- AbruptChangeGenerator - Class in moa.streams.generators.cd
-
- AbruptChangeGenerator() - Constructor for class moa.streams.generators.cd.AbruptChangeGenerator
-
- absorbCluster(GridCluster) - Method in class moa.clusterers.dstream.GridCluster
-
- AbstractAMRules - Class in moa.classifiers.rules
-
- AbstractAMRules() - Constructor for class moa.classifiers.rules.AbstractAMRules
-
- AbstractAMRules(double) - Constructor for class moa.classifiers.rules.AbstractAMRules
-
- AbstractAMRulesFunctionBasicMlLearner - Class in moa.classifiers.rules.multilabel.functions
-
- AbstractAMRulesFunctionBasicMlLearner() - Constructor for class moa.classifiers.rules.multilabel.functions.AbstractAMRulesFunctionBasicMlLearner
-
- AbstractAnomalyDetector - Class in moa.classifiers.rules.core.anomalydetection
-
- AbstractAnomalyDetector() - Constructor for class moa.classifiers.rules.core.anomalydetection.AbstractAnomalyDetector
-
- AbstractC - Class in moa.clusterers.outliers.AbstractC
-
- AbstractC() - Constructor for class moa.clusterers.outliers.AbstractC.AbstractC
-
- AbstractCBase - Class in moa.clusterers.outliers.AbstractC
-
- AbstractCBase() - Constructor for class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- AbstractChangeDetector - Class in moa.classifiers.core.driftdetection
-
Abstract Change Detector.
- AbstractChangeDetector() - Constructor for class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
- AbstractClassifier - Class in moa.classifiers
-
- AbstractClassifier() - Constructor for class moa.classifiers.AbstractClassifier
-
Creates an classifier and setups the random seed option
if the classifier is randomizable.
- AbstractClassOption - Class in com.github.javacliparser
-
Abstract class option.
- AbstractClassOption - Class in moa.options
-
Abstract class option.
- AbstractClassOption(String, char, String, Class<?>, String) - Constructor for class com.github.javacliparser.AbstractClassOption
-
Creates a new instance of an abstract option given its class name,
command line interface text, its purpose, its class type and its default
command line interface text.
- AbstractClassOption(String, char, String, Class<?>, String) - Constructor for class moa.options.AbstractClassOption
-
Creates a new instance of an abstract option given its class name,
command line interface text, its purpose, its class type and its default
command line interface text.
- AbstractClassOption(String, char, String, Class<?>, String, String) - Constructor for class com.github.javacliparser.AbstractClassOption
-
Creates a new instance of an abstract option given its class name,
command line interface text, its purpose, its class type, default
command line interface text, and its null text.
- AbstractClassOption(String, char, String, Class<?>, String, String) - Constructor for class moa.options.AbstractClassOption
-
Creates a new instance of an abstract option given its class name,
command line interface text, its purpose, its class type, default
command line interface text, and its null text.
- AbstractClusterer - Class in moa.clusterers
-
- AbstractClusterer() - Constructor for class moa.clusterers.AbstractClusterer
-
- AbstractConceptDriftGenerator - Class in moa.streams.generators.cd
-
- AbstractConceptDriftGenerator() - Constructor for class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- AbstractErrorWeightedVote - Class in moa.classifiers.rules.core.voting
-
AbstractErrorWeightedVote class for weighted votes based on estimates of errors.
- AbstractErrorWeightedVote() - Constructor for class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
-
- AbstractErrorWeightedVoteMultiLabel - Class in moa.classifiers.rules.multilabel.core.voting
-
AbstractErrorWeightedVote class for weighted votes based on estimates of errors.
- AbstractErrorWeightedVoteMultiLabel() - Constructor for class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- AbstractFeatureRanking - Class in moa.classifiers.rules.featureranking
-
- AbstractFeatureRanking() - Constructor for class moa.classifiers.rules.featureranking.AbstractFeatureRanking
-
- AbstractGraphAxes - Class in moa.gui.visualization
-
AbstractGraphAxes is an abstract class offering functionality to draw axes.
- AbstractGraphAxes() - Constructor for class moa.gui.visualization.AbstractGraphAxes
-
Initialises a AbstractGraphAxes by setting the initial values and the
layout.
- AbstractGraphCanvas - Class in moa.gui.visualization
-
AbstractGraphCanvas is an abstract class offering scaling functionality and
the structure of the underlying Axes and Plot classes.
- AbstractGraphCanvas(AbstractGraphAxes, AbstractGraphPlot) - Constructor for class moa.gui.visualization.AbstractGraphCanvas
-
Initialises an AbstractGraphCanvas by constructing its AbstractGraphAxes,
AbstractGraphPlot as well as setting initial sizes.
- AbstractGraphPlot - Class in moa.gui.visualization
-
AbstractGraphPlot is an abstract class defining the structure of a Plot
class.
- AbstractGraphPlot() - Constructor for class moa.gui.visualization.AbstractGraphPlot
-
- AbstractMacroClusterer - Class in moa.clusterers.macro
-
- AbstractMacroClusterer() - Constructor for class moa.clusterers.macro.AbstractMacroClusterer
-
- AbstractMOAObject - Class in moa
-
Abstract MOA Object.
- AbstractMOAObject() - Constructor for class moa.AbstractMOAObject
-
- AbstractMultiLabelErrorMeasurer - Class in moa.classifiers.rules.multilabel.errormeasurers
-
- AbstractMultiLabelErrorMeasurer() - Constructor for class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiLabelErrorMeasurer
-
- AbstractMultiLabelLearner - Class in moa.classifiers
-
- AbstractMultiLabelLearner() - Constructor for class moa.classifiers.AbstractMultiLabelLearner
-
- AbstractMultiLabelStreamFilter - Class in moa.streams.filters
-
Abstract Stream Filter.
- AbstractMultiLabelStreamFilter() - Constructor for class moa.streams.filters.AbstractMultiLabelStreamFilter
-
- AbstractMultiTargetErrorMeasurer - Class in moa.classifiers.rules.multilabel.errormeasurers
-
- AbstractMultiTargetErrorMeasurer() - Constructor for class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiTargetErrorMeasurer
-
- AbstractOption - Class in com.github.javacliparser
-
Abstract option.
- AbstractOption(String, char, String) - Constructor for class com.github.javacliparser.AbstractOption
-
Creates a new instance of an abstract option given its class name,
command line interface text and its purpose.
- AbstractOptionHandler - Class in moa.options
-
Abstract Option Handler.
- AbstractOptionHandler() - Constructor for class moa.options.AbstractOptionHandler
-
- AbstractRecommenderData - Class in moa.recommender.rc.data
-
- AbstractRecommenderData() - Constructor for class moa.recommender.rc.data.AbstractRecommenderData
-
- AbstractStreamFilter - Class in moa.streams.filters
-
Abstract Stream Filter.
- AbstractStreamFilter() - Constructor for class moa.streams.filters.AbstractStreamFilter
-
- AbstractTabPanel - Class in moa.gui
-
Abstract Tab Panel.
- AbstractTabPanel() - Constructor for class moa.gui.AbstractTabPanel
-
- AbstractTask - Class in moa.tasks
-
Abstract Task.
- AbstractTask() - Constructor for class moa.tasks.AbstractTask
-
- acc1 - Variable in class moa.gui.experimentertab.TaskTextViewerPanel
-
- acc1 - Variable in class moa.gui.TaskTextViewerPanel
-
- acc2 - Variable in class moa.gui.experimentertab.TaskTextViewerPanel
-
- acc2 - Variable in class moa.gui.TaskTextViewerPanel
-
- accBal - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- accept(File) - Method in class moa.gui.FileExtensionFilter
-
- acceptsInstances() - Method in class moa.gui.featureanalysis.FeatureImportancePanel
-
We can accept instances
- accLearner - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- accReset - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- accResetBal - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- accumulatedError - Variable in class moa.classifiers.rules.functions.Perceptron
-
- Accuracy - Class in moa.evaluation
-
- Accuracy() - Constructor for class moa.evaluation.Accuracy
-
- accuracyBaseLearner - Variable in class moa.classifiers.active.ALUncertainty
-
- AccuracyUpdatedEnsemble - Class in moa.classifiers.meta
-
The revised version of the Accuracy Updated Ensemble as proposed by
Brzezinski and Stefanowski in "Reacting to Different Types of Concept Drift:
The Accuracy Updated Ensemble Algorithm", IEEE Trans.
- AccuracyUpdatedEnsemble() - Constructor for class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
- AccuracyWeightedEnsemble - Class in moa.classifiers.meta
-
The Accuracy Weighted Ensemble classifier as proposed by Wang et al.
- AccuracyWeightedEnsemble() - Constructor for class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- actionPerformed(ActionEvent) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- actionPerformed(ActionEvent) - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- actionPerformed(ActionEvent) - Method in class moa.gui.experimentertab.TaskTextViewerPanel
-
- actionPerformed(ActionEvent) - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- actionPerformed(ActionEvent) - Method in class moa.gui.outliertab.OutlierVisualTab
-
- actionPerformed(ActionEvent) - Method in class moa.gui.TaskTextViewerPanel
-
- actionPerformed(ActionEvent) - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- actionPerformed(ActionEvent) - Method in class moa.gui.visualization.RunVisualizer
-
- activateLearningNode(EFDT.InactiveLearningNode, EFDT.SplitNode, int) - Method in class moa.classifiers.trees.EFDT
-
- activateLearningNode(HoeffdingOptionTree.InactiveLearningNode, HoeffdingOptionTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- activateLearningNode(HoeffdingTree.InactiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingTree
-
- activeClassifiersOption - Variable in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- activeLeafByteSizeEstimate - Variable in class moa.classifiers.trees.EFDT
-
- activeLeafByteSizeEstimate - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- activeLeafByteSizeEstimate - Variable in class moa.classifiers.trees.HoeffdingTree
-
- activeLeafNodeCount - Variable in class moa.classifiers.trees.EFDT
-
- activeLeafNodeCount - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- activeLeafNodeCount - Variable in class moa.classifiers.trees.HoeffdingTree
-
- ActiveLearningNode(double[]) - Constructor for class moa.classifiers.trees.EFDT.ActiveLearningNode
-
- ActiveLearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
-
- ActiveLearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
-
- activeLearningStrategyOption - Variable in class moa.classifiers.active.ALUncertainty
-
- actualClassStatistics - Variable in class moa.classifiers.rules.RuleClassification
-
- acuityOption - Variable in class moa.clusterers.CobWeb
-
- ADACC - Class in moa.classifiers.meta
-
Anticipative and Dynamic Adaptation to Concept Changes.
- ADACC() - Constructor for class moa.classifiers.meta.ADACC
-
- AdaGrad - Class in moa.classifiers.functions
-
Implements the AdaGrad oneline optimiser for learning various linear models (binary class SVM, binary class logistic regression and linear regression).
- AdaGrad() - Constructor for class moa.classifiers.functions.AdaGrad
-
- AdaHoeffdingOptionTree - Class in moa.classifiers.trees
-
Adaptive decision option tree for streaming data with adaptive Naive
Bayes classification at leaves.
- AdaHoeffdingOptionTree() - Constructor for class moa.classifiers.trees.AdaHoeffdingOptionTree
-
- AdaHoeffdingOptionTree.AdaLearningNode - Class in moa.classifiers.trees
-
- AdaLearningNode(double[]) - Constructor for class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
-
- AdaLearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- AdaptiveLeafNode(Iadem3, Iadem2.Node, long, long, double[], IademNumericAttributeObserver, AbstractChangeDetector, boolean, boolean, Instance) - Constructor for class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNode
-
- AdaptiveLeafNodeNB(Iadem3, Iadem2.Node, long, long, double[], IademNumericAttributeObserver, int, AbstractChangeDetector, boolean, boolean, Instance) - Constructor for class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNB
-
- AdaptiveLeafNodeNBAdaptive(Iadem3, Iadem2.Node, long, long, double[], IademNumericAttributeObserver, int, boolean, boolean, AbstractChangeDetector, Instance) - Constructor for class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNBAdaptive
-
- AdaptiveLeafNodeNBKirkby(Iadem3, Iadem2.Node, long, long, double[], IademNumericAttributeObserver, int, boolean, boolean, AbstractChangeDetector, Instance) - Constructor for class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNBKirkby
-
- AdaptiveLeafNodeWeightedVote(Iadem3, Iadem2.Node, long, long, double[], IademNumericAttributeObserver, int, boolean, boolean, AbstractChangeDetector, Instance) - Constructor for class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeWeightedVote
-
- AdaptiveMultiTargetRegressor - Class in moa.classifiers.rules.multilabel.functions
-
Adaptive MultiTarget Regressor uses two learner
The first is used in first stage when high error are produced(e.g.
- AdaptiveMultiTargetRegressor() - Constructor for class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- AdaptiveNodePredictor - Class in moa.classifiers.rules.functions
-
- AdaptiveNodePredictor() - Constructor for class moa.classifiers.rules.functions.AdaptiveNodePredictor
-
- AdaptiveNominalVirtualNode(Iadem3, Iadem2.Node, int, boolean, boolean) - Constructor for class moa.classifiers.trees.iadem.Iadem3.AdaptiveNominalVirtualNode
-
- AdaptiveNumericVirtualNode(Iadem3, Iadem2.Node, int, IademNumericAttributeObserver) - Constructor for class moa.classifiers.trees.iadem.Iadem3.AdaptiveNumericVirtualNode
-
- AdaptiveRandomForest - Class in moa.classifiers.meta
-
Adaptive Random Forest
- AdaptiveRandomForest() - Constructor for class moa.classifiers.meta.AdaptiveRandomForest
-
- AdaptiveRandomForest.ARFBaseLearner - Class in moa.classifiers.meta
-
Inner class that represents a single tree member of the forest.
- AdaptiveRandomForest.TrainingRunnable - Class in moa.classifiers.meta
-
Inner class to assist with the multi-thread execution.
- AdaptiveRandomForestRegressor - Class in moa.classifiers.meta
-
Implementation of AdaptiveRandomForestRegressor, an extension of AdaptiveRandomForest for classification.
- AdaptiveRandomForestRegressor() - Constructor for class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner - Class in moa.classifiers.meta
-
- AdaptiveSplitNode(Iadem3, Iadem2.Node, Iadem2.Node[], double[], InstanceConditionalTest, AbstractChangeDetector, Iadem3.AdaptiveLeafNode, int) - Constructor for class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- AdaSplitNode(InstanceConditionalTest, double[]) - Constructor for class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- AdaSplitNode(InstanceConditionalTest, double[], int) - Constructor for class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- add(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- add(double) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Block
-
- add(double) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- add(double) - Method in class moa.evaluation.AdwinClassificationPerformanceEvaluator.AdwinEstimator
-
- add(double) - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.SimpleEstimator
-
- add(double) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator.BasicEstimator
-
- add(double) - Method in interface moa.evaluation.BasicClassificationPerformanceEvaluator.Estimator
-
- add(double) - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator.EWMAEstimator
-
- add(double) - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator.FadingFactorEstimator
-
- add(double) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator.Estimator
-
- add(double) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator.Estimator
-
- add(double) - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.SimpleEstimator
-
- add(double) - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator.WindowEstimator
-
- add(double) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
-
- add(double, boolean) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- add(double, boolean, boolean) - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- add(double, boolean, boolean) - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- add(int) - Method in class moa.streams.filters.Selection
-
- add(int, double[], double) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Adds a point to the ClusteringFeature.
- add(int, int) - Method in class moa.streams.filters.Selection
-
- add(int, T) - Method in class moa.core.AutoExpandVector
-
- add(Instance) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Adds the.
- add(DATA) - Method in class moa.clusterers.outliers.utils.mtree.MTree
-
Adds and indexes a data object.
- add(E) - Method in class moa.core.FixedLengthList
-
Calls super.add(entry) to append the entry to the end of the FixedLengthList.
- add(CFCluster) - Method in class moa.cluster.CFCluster
-
- add(CFCluster) - Method in class moa.clusterers.clustream.ClustreamKernel
-
- add(Cluster) - Method in class moa.cluster.Clustering
-
add a cluster to the clustering
- add(ClusKernel) - Method in class moa.clusterers.clustree.ClusKernel
-
Adds the given cluster to this cluster, without making this cluster
older.
- add(Entry) - Method in class moa.clusterers.clustree.Entry
-
Add the data cluster of another entry to the data cluster of this entry.
- add(T) - Method in class moa.core.AutoExpandVector
-
- addAll(int, Collection<? extends T>) - Method in class moa.core.AutoExpandVector
-
- addAll(Collection<? extends E>) - Method in class moa.core.FixedLengthList
-
Appends all of the elements in the argument collection in the order that they are returned by the collection's iterator.
- addAll(Collection<? extends T>) - Method in class moa.core.AutoExpandVector
-
- addAt(int, double) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Block
-
- addAt(int, double) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- addBlockToHead(SEEDChangeDetector.SEEDBlock) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- addBlockToTail(SEEDChangeDetector.SEEDBlock) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- addButtonActionListener(ActionListener) - Method in class moa.gui.clustertab.ClusteringSetupTab
-
- addButtonActionListener(ActionListener) - Method in class moa.gui.outliertab.OutlierSetupTab
-
- addCapabilities(Collection<Capability>) - Method in class moa.capabilities.Capabilities
-
Augments this capabilities object with the given capabilities.
- addCapabilities(Collection<Capability>) - Method in class moa.capabilities.ImmutableCapabilities
-
- addCapabilities(Capabilities) - Method in class moa.capabilities.Capabilities
-
Augments this capabilities object with the given capabilities.
- addCapabilities(Capabilities) - Method in class moa.capabilities.ImmutableCapabilities
-
- addCapabilities(Capability...) - Method in class moa.capabilities.Capabilities
-
Augments this capabilities object with the given capabilities.
- addCapabilities(Capability...) - Method in class moa.capabilities.ImmutableCapabilities
-
- addCapability(Capability) - Method in class moa.capabilities.Capabilities
-
Augments this capabilities object with the given capability.
- addCapability(Capability) - Method in class moa.capabilities.ImmutableCapabilities
-
- addChangeListener(ChangeListener) - Method in class com.github.javacliparser.gui.ClassOptionEditComponent
-
Adds the listener to the internal set of listeners.
- addChangeListener(ChangeListener) - Method in class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
Adds the listener to the internal set of listeners.
- addChild(Iadem2.Node) - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- addChild(ClusteringTreeNode) - Method in class moa.clusterers.kmeanspm.ClusteringTreeHeadNode
-
- addChild(ClusteringTreeNode) - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Adds a child node.
- addClusterChangeListener(ClusterEventListener) - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
Add a listener
- addCode() - Method in class moa.tasks.ipynb.NotebookBuilder
-
- addedPermanent - Variable in class moa.classifiers.meta.ADACC
-
Number of added snapshots
- addElement(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEED
-
- addElement(double) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Reservoir
-
- addElement(E) - Method in class moa.core.FastVector
-
Adds an element to this vector.
- addEmptyValue(int) - Method in class moa.evaluation.MeasureCollection
-
- addEntry(Entry, long) - Method in class moa.clusterers.clustree.Node
-
Add a new Entry to this node.
- addEventType(String) - Method in class moa.evaluation.MeasureCollection
-
- addGrid(DensityGrid) - Method in class moa.clusterers.dstream.GridCluster
-
- addInstanceInfo(Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Adds one instance to KDTree loosly.
- addInstanceInfo(Instance) - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch
-
Adds the given instance info.
- addInstanceInfo(Instance) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Adds information from the given instance without modifying the
datastructure a lot.
- addInstanceToTree(Instance, KDTreeNode) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Recursively adds an instance to the tree starting from
the supplied KDTreeNode.
- addItem(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.data.AbstractRecommenderData
-
- addItem(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- addItem(int, List<Integer>, List<Double>) - Method in interface moa.recommender.rc.data.RecommenderData
-
- additionalPlotOption - Variable in class moa.tasks.Plot
-
Additional plot options.
- additionalSetOption - Variable in class moa.tasks.Plot
-
Addition pre-plot gunplot commands.
- addLiteralAttribute(int) - Method in class moa.classifiers.rules.featureranking.WeightedMajorityFeatureRanking.RuleInformation
-
- addMarkdown() - Method in class moa.tasks.ipynb.NotebookBuilder
-
- addMeasurementName(String) - Method in class moa.evaluation.preview.LearningCurve
-
- addMerit(int, double) - Method in class moa.classifiers.rules.featureranking.BasicFeatureRanking.RuleInformation
-
- AddNode(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.MicroCluster
-
- AddNoiseFilter - Class in moa.streams.filters
-
Filter for adding random noise to examples in a stream.
- AddNoiseFilter() - Constructor for class moa.streams.filters.AddNoiseFilter
-
- addNoiseOption - Variable in class moa.streams.generators.WaveformGenerator
-
- addNumLiterals() - Method in class moa.classifiers.rules.featureranking.MeritFeatureRanking.RuleInformation
-
- addObject(DataObject) - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
Adds a DataObject to the set.
- addObject(DataSet) - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
Adds all objects in the given data set
- addObservation(double, double) - Method in class moa.core.GaussianEstimator
-
- addObservations(GaussianEstimator) - Method in class moa.core.GaussianEstimator
-
- addObserver(ObserverMOAObject) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- addObserver(ObserverMOAObject) - Method in class moa.classifiers.rules.multilabel.core.ObservableMOAObject
-
- addOldLabel(double) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
-
- addOption(Option) - Method in class com.github.javacliparser.Options
-
- AddOutlier(MyBaseOutlierDetector.Outlier) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- AddPrecNeigh(Long) - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM.ISBNodeExact
-
- AddPrecNeigh(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- AddPrecNeigh(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- addPrediction(double[], Instance) - Method in class moa.classifiers.rules.errormeasurers.ErrorMeasurement
-
- addPrediction(double[], Instance) - Method in class moa.classifiers.rules.errormeasurers.MeanAbsoluteDeviation
-
- addPrediction(double[], Instance) - Method in class moa.classifiers.rules.errormeasurers.RootMeanSquaredError
-
- addPrediction(Prediction, MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiLabelErrorMeasurer
-
- addPrediction(Prediction, MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiTargetErrorMeasurer
-
- addPrediction(Prediction, MultiLabelInstance) - Method in interface moa.classifiers.rules.multilabel.errormeasurers.MultiLabelErrorMeasurer
-
- addPrediction(Prediction, Prediction) - Method in class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiLabelErrorMeasurer
-
- addPrediction(Prediction, Prediction) - Method in interface moa.classifiers.rules.multilabel.errormeasurers.MultiLabelErrorMeasurer
-
- addPrediction(Prediction, Prediction, double) - Method in class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiLabelErrorMeasurer
-
- addPrediction(Prediction, Prediction, double) - Method in class moa.classifiers.rules.multilabel.errormeasurers.MeanAbsoluteDeviationMT
-
- addPrediction(Prediction, Prediction, double) - Method in interface moa.classifiers.rules.multilabel.errormeasurers.MultiLabelErrorMeasurer
-
- addPrediction(Prediction, Prediction, double) - Method in class moa.classifiers.rules.multilabel.errormeasurers.RelativeMeanAbsoluteDeviationMT
-
- addPrediction(Prediction, Prediction, double) - Method in class moa.classifiers.rules.multilabel.errormeasurers.RelativeRootMeanSquaredErrorMT
-
- addPrediction(Prediction, Prediction, double) - Method in class moa.classifiers.rules.multilabel.errormeasurers.RootMeanSquaredErrorMT
-
- addPropertyChangeListener(PropertyChangeListener) - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Adds a PropertyChangeListener who will be notified of value changes.
- addRaw() - Method in class moa.tasks.ipynb.NotebookBuilder
-
- addResult(E, double[]) - Method in interface moa.evaluation.LearningPerformanceEvaluator
-
Adds a learning result to this evaluator.
- addResult(E, Prediction) - Method in interface moa.evaluation.LearningPerformanceEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.BasicMultiLabelPerformanceEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator
-
- addResult(Example<Instance>, double[]) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.BasicMultiLabelPerformanceEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator
-
- addResult(Example<Instance>, Prediction) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- addSource(String) - Method in class moa.tasks.ipynb.NotebookCellBuilder
-
Appends a line of source to cell on a new separate line.
- addSparseValues(int[], double[], int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Adds the sparse values.
- addSparseValues(int[], double[], int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Adds the sparse values.
- addSubtree(Iadem3Subtree) - Method in class moa.classifiers.trees.iadem.Iadem3
-
- addSubtree(Iadem3Subtree) - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- addTaskCompletionListener(TaskCompletionListener) - Method in class moa.gui.experimentertab.ExpTaskThread
-
- addTaskCompletionListener(TaskCompletionListener) - Method in class moa.tasks.TaskThread
-
- addText(String) - Method in class moa.gui.TextViewerPanel
-
- addTimePerObject(double) - Method in class moa.evaluation.OutlierPerformance
-
- addToClustering(Clustering) - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Adds all ClusterFeatures of the tree with this node as the root to a
Clustering.
- addToClusteringCenters(List<double[]>) - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Adds all clustering centers of the ClusterFeatures of the tree with this
node as the root to a List of points.
- addToSplitAttempts(int) - Method in class moa.classifiers.trees.EFDT.Node
-
- addToStored(Classifier, double) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Adds a classifier to the storage.
- addToStored(Classifier, double) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Adds a classifier to the storage.
- addToStored(OnlineAccuracyUpdatedEnsemble.ClassifierWithMemory, double) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Adds a classifier to the storage.
- addToValue(int, double) - Method in class moa.core.DoubleVector
-
- addToValue(int, float) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- addToValues(double) - Method in class moa.core.DoubleVector
-
- addToValues(float) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- addTransaction(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- addUndeclaredValuesOption - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelNominalAttributeObserver
-
- addUser(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.data.AbstractRecommenderData
-
- addUser(int, List<Integer>, List<Double>) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- addUser(int, List<Integer>, List<Double>) - Method in interface moa.recommender.rc.data.RecommenderData
-
- addValue(double, int, double) - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- addValue(double, int, double) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- addValue(double, int, double) - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- addValue(double, int, double) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- addValue(int, double) - Method in class moa.evaluation.MeasureCollection
-
- addValue(String, double) - Method in class moa.evaluation.MeasureCollection
-
- addValues(double[]) - Method in class moa.core.DoubleVector
-
- addValues(float[]) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- addValues(SingleVector) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- addValues(DoubleVector) - Method in class moa.core.DoubleVector
-
- addVectors(double[], double[]) - Static method in class moa.cluster.CFCluster
-
Adds the second array to the first array element by element.
- addVote(double[], double) - Method in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
-
- addVote(double[], double) - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote
-
Adds a vote and the corresponding error for the computation of the weighted vote and respective weighted error.
- addVote(Prediction, double[]) - Method in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- addVote(Prediction, double[]) - Method in interface moa.classifiers.rules.multilabel.core.voting.ErrorWeightedVoteMultiLabel
-
Adds a vote and the corresponding error for the computation of the weighted vote and respective weighted error.
- ADError - Variable in class moa.classifiers.meta.LeveragingBag
-
- ADError - Variable in class moa.classifiers.meta.LimAttClassifier
-
- ADError - Variable in class moa.classifiers.meta.OzaBagAdwin
-
- ADError - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- adjustAlgorithm(boolean, boolean, int) - Method in class moa.clusterers.meta.Algorithm
-
- adjustEnsembleSize(int) - Method in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- adjustEnsembleSize(int) - Method in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- adjustEnsembleSize(int) - Method in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- adjustEnsembleSize(int) - Method in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- adjustEnsembleSize(int) - Method in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- adjustEnsembleSize(int) - Method in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- adjustParameters() - Method in class moa.clusterers.AbstractClusterer
-
- adjustParameters() - Method in class moa.clusterers.clustream.WithKmeans
-
- adjustParameters() - Method in class moa.clusterers.clustree.ClusTree
-
- adjustParameters() - Method in class moa.clusterers.denstream.WithDBSCAN
-
- adjustParameters() - Method in class moa.clusterers.dstream.Dstream
-
- ADOB - Class in moa.classifiers.meta
-
Adaptable Diversity-based Online Boosting (ADOB) is a modified version
of the online boosting, as proposed by Oza and Russell, which is aimed
at speeding up the experts recovery after concept drifts.
- ADOB() - Constructor for class moa.classifiers.meta.ADOB
-
- adwin - Variable in class moa.classifiers.core.driftdetection.ADWINChangeDetector
-
- adwin - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- adwin - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- adwin - Variable in class moa.evaluation.AdwinClassificationPerformanceEvaluator.AdwinEstimator
-
- ADWIN - Class in moa.classifiers.core.driftdetection
-
ADaptive sliding WINdow method.
- ADWIN() - Constructor for class moa.classifiers.core.driftdetection.ADWIN
-
- ADWIN(double) - Constructor for class moa.classifiers.core.driftdetection.ADWIN
-
- ADWIN(int) - Constructor for class moa.classifiers.core.driftdetection.ADWIN
-
- ADWINChangeDetector - Class in moa.classifiers.core.driftdetection
-
Drift detection method based in ADWIN.
- ADWINChangeDetector() - Constructor for class moa.classifiers.core.driftdetection.ADWINChangeDetector
-
- AdwinClassificationPerformanceEvaluator - Class in moa.evaluation
-
Classification evaluator that updates evaluation results using an adaptive sliding
window.
- AdwinClassificationPerformanceEvaluator() - Constructor for class moa.evaluation.AdwinClassificationPerformanceEvaluator
-
- AdwinClassificationPerformanceEvaluator.AdwinEstimator - Class in moa.evaluation
-
- adwinDriftDetector - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- adwinEnsemble - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- adwinEnsemble - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- adwinEnsemble - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- adwinEnsemble - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- adwinEnsemble - Variable in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- adwinEnsemble - Variable in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- AdwinEstimator() - Constructor for class moa.evaluation.AdwinClassificationPerformanceEvaluator.AdwinEstimator
-
- adwinReplaceWorstClassifierOption - Variable in class moa.classifiers.meta.LimAttClassifier
-
- afterAddInstance(KDTreeNode) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Corrects the start and end indices of a
KDTreeNode after an instance is added to
the tree.
- aggregate(ClusKernel, long, double) - Method in class moa.clusterers.clustree.ClusKernel
-
Make this cluster older bei weighting it and add to this cluster the
given cluster.
- aggregateCluster(ClusKernel, long, double) - Method in class moa.clusterers.clustree.Entry
-
Aggregate the given Kernel to the data cluster
of this entry.
- aggregateEntry(Entry, long, double) - Method in class moa.clusterers.clustree.Entry
-
Aggregate the data in the Kernel of the other
Entry.
- aggregateToBuffer(ClusKernel, long, double) - Method in class moa.clusterers.clustree.Entry
-
Aggregate the given Kernel to the buffer
cluster of this entry.
- AgrawalGenerator - Class in moa.streams.generators
-
Stream generator for Agrawal dataset.
- AgrawalGenerator() - Constructor for class moa.streams.generators.AgrawalGenerator
-
- AgrawalGenerator.ClassFunction - Interface in moa.streams.generators
-
- ALClassificationPerformanceEvaluator - Interface in moa.evaluation
-
Active Learning Evaluator Interface to make AL Evaluators selectable in AL tasks.
- ALClassifier - Interface in moa.classifiers.active
-
Active Learning Classifier Interface to make AL Classifiers selectable in AL tasks.
- algName - Variable in class moa.gui.experimentertab.statisticaltests.RankPerAlgorithm
-
- algName1 - Variable in class moa.gui.experimentertab.statisticaltests.PValuePerTwoAlgorithm
-
- algName2 - Variable in class moa.gui.experimentertab.statisticaltests.PValuePerTwoAlgorithm
-
- algNames - Variable in class moa.gui.experimentertab.SummaryTable
-
- algorithm - Variable in class moa.clusterers.meta.Algorithm
-
- algorithm - Variable in class moa.gui.experimentertab.Stream
-
The list of algorithms within of the stream
- Algorithm - Class in moa.clusterers.meta
-
- Algorithm - Class in moa.gui.experimentertab
-
This class calculates the different measures for each algorithm
- Algorithm(String, List<Measure>, BufferedReader, String) - Constructor for class moa.gui.experimentertab.Algorithm
-
Algorithm constructor
- Algorithm(AlgorithmConfiguration) - Constructor for class moa.clusterers.meta.Algorithm
-
- Algorithm(Algorithm, double, double, boolean, boolean, int) - Constructor for class moa.clusterers.meta.Algorithm
-
- algorithmImplementation - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- algorithmImplementationOption - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- algoritmModel - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- allAttUsed - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- ALMainTask - Class in moa.tasks.meta
-
This class provides a superclass for Active Learning tasks, which
enables convenient searching for those tasks for example when showing
a list of available Active Learning tasks.
- ALMainTask() - Constructor for class moa.tasks.meta.ALMainTask
-
- ALMeasureCollection - Class in moa.evaluation
-
Collection of measures used to evaluate AL tasks.
- ALMeasureCollection() - Constructor for class moa.evaluation.ALMeasureCollection
-
- ALMultiParamTask - Class in moa.tasks.meta
-
This task individually evaluates an active learning classifier for each
element of a set of parameter values.
- ALMultiParamTask() - Constructor for class moa.tasks.meta.ALMultiParamTask
-
Default constructor which sets up the refresh mechanism between the
learner and the variedParamName option.
- ALMultiParamTask(Color[]) - Constructor for class moa.tasks.meta.ALMultiParamTask
-
Constructor that sets the color coding for the subtasks additionally
to the default constructor.
- ALPartitionEvaluationTask - Class in moa.tasks.meta
-
This task extensively evaluates an active learning classifier on a stream.
- ALPartitionEvaluationTask() - Constructor for class moa.tasks.meta.ALPartitionEvaluationTask
-
- alpha - Variable in class moa.classifiers.meta.OCBoost
-
- alpha - Variable in class moa.classifiers.meta.OnlineSmoothBoost
-
- alpha - Variable in class moa.classifiers.meta.OzaBagASHT
-
- alpha - Variable in class moa.classifiers.rules.core.Rule.Builder
-
- alpha - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
-
- alpha - Variable in class moa.classifiers.rules.functions.LowPassFilteredLearner
-
- alpha - Variable in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
-
- alpha - Variable in class moa.evaluation.EWMAClassificationPerformanceEvaluator.EWMAEstimator
-
- alpha - Variable in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator.FadingFactorEstimator
-
- alpha(double) - Method in class moa.classifiers.rules.core.Rule.Builder
-
- alphaDriftOption - Variable in class moa.classifiers.core.driftdetection.STEPD
-
- alphainc - Variable in class moa.classifiers.meta.OCBoost
-
- alphaOption - Variable in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
-
- alphaOption - Variable in class moa.classifiers.core.driftdetection.PageHinkleyDM
-
- alphaOption - Variable in class moa.classifiers.meta.HeterogeneousEnsembleBlastFadingFactors
-
- alphaOption - Variable in class moa.classifiers.rules.functions.LowPassFilteredLearner
-
- alphaOption - Variable in class moa.evaluation.EWMAClassificationPerformanceEvaluator
-
- alphaOption - Variable in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
-
- alphaOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequential
-
- alphaOption - Variable in class moa.streams.ConceptDriftRealStream
-
- alphaOption - Variable in class moa.streams.ConceptDriftStream
-
- alphaOption - Variable in class moa.tasks.EvaluatePrequential
-
- alphaOption - Variable in class moa.tasks.EvaluatePrequentialDelayed
-
- alphaOption - Variable in class moa.tasks.EvaluatePrequentialMultiLabel
-
- alphaOption - Variable in class moa.tasks.EvaluatePrequentialMultiTarget
-
- alphaOption - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- alphaOption - Variable in class moa.tasks.EvaluatePrequentialRegression
-
- alphaSEEDOption - Variable in class moa.classifiers.core.driftdetection.SEEDChangeDetector
-
- alphaWarningOption - Variable in class moa.classifiers.core.driftdetection.STEPD
-
- ALPrequentialEvaluationTask - Class in moa.tasks.meta
-
This task performs prequential evaluation for an active learning classifier
(testing, then training with each example in sequence).
- ALPrequentialEvaluationTask() - Constructor for class moa.tasks.meta.ALPrequentialEvaluationTask
-
Constructor which sets the color coding to black.
- ALPrequentialEvaluationTask(Color) - Constructor for class moa.tasks.meta.ALPrequentialEvaluationTask
-
Constructor with which a color coding can be set.
- ALPreviewPanel - Class in moa.gui.active
-
ALPreviewPanel provides a graphical interface to display the latest preview
of a task thread.
- ALPreviewPanel() - Constructor for class moa.gui.active.ALPreviewPanel
-
Initialises the underlying ALTaskTextViewerPanel and the refresh components.
- ALRandom - Class in moa.classifiers.active
-
- ALRandom() - Constructor for class moa.classifiers.active.ALRandom
-
- alreadyUsed - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- alreadyUsed - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- ALTabPanel - Class in moa.gui
-
This panel allows the user to select and configure a task, and run it.
- ALTabPanel() - Constructor for class moa.gui.ALTabPanel
-
- ALTaskManagerPanel - Class in moa.gui.active
-
This panel displays the running tasks for active learning experiments.
- ALTaskManagerPanel() - Constructor for class moa.gui.active.ALTaskManagerPanel
-
- ALTaskManagerPanel.ProgressCellRenderer - Class in moa.gui.active
-
- ALTaskManagerPanel.TaskColorCodingCellRenderer - Class in moa.gui.active
-
- ALTaskManagerPanel.TaskTableModel - Class in moa.gui.active
-
- ALTaskTextViewerPanel - Class in moa.gui.active
-
This panel displays text.
- ALTaskTextViewerPanel() - Constructor for class moa.gui.active.ALTaskTextViewerPanel
-
- ALTaskThread - Class in moa.tasks.meta
-
Task Thread for ALMainTask which supports pausing/resuming and cancelling of child threads
- ALTaskThread(Task) - Constructor for class moa.tasks.meta.ALTaskThread
-
- ALTaskThread(Task, ObjectRepository) - Constructor for class moa.tasks.meta.ALTaskThread
-
- altAttClassObserver - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveNumericVirtualNode
-
- altClassDist - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveNumericVirtualNode
-
- alternateTree - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- alternateTree - Variable in class moa.classifiers.trees.ARFFIMTDD.Node
-
- alternateTree - Variable in class moa.classifiers.trees.FIMTDD.Node
-
- alternateTree - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- alternateTreeFadingFactorOption - Variable in class moa.classifiers.multilabel.trees.ISOUPTree
-
- alternateTreeFadingFactorOption - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- alternateTreeFadingFactorOption - Variable in class moa.classifiers.trees.FIMTDD
-
- alternateTrees - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree
-
- alternateTreeTimeOption - Variable in class moa.classifiers.multilabel.trees.ISOUPTree
-
- alternateTreeTimeOption - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- alternateTreeTimeOption - Variable in class moa.classifiers.trees.FIMTDD
-
- alternateTreeTMinOption - Variable in class moa.classifiers.multilabel.trees.ISOUPTree
-
- alternateTreeTMinOption - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- alternateTreeTMinOption - Variable in class moa.classifiers.trees.FIMTDD
-
- alternativeTree - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- ALUncertainty - Class in moa.classifiers.active
-
Active learning setting for evolving data streams.
- ALUncertainty() - Constructor for class moa.classifiers.active.ALUncertainty
-
- ALWAYS_SEND_INSTANCES_TO_ALL - Static variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel.PreprocessDefaults
-
- ALWAYS_SEND_INSTANCES_TO_ALL_KEY - Static variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel.PreprocessDefaults
-
- ALWindowClassificationPerformanceEvaluator - Class in moa.evaluation
-
Active Learning Wrapper for BasicClassificationPerformanceEvaluator.
- ALWindowClassificationPerformanceEvaluator() - Constructor for class moa.evaluation.ALWindowClassificationPerformanceEvaluator
-
- amountValues - Static variable in class moa.streams.generators.AssetNegotiationGenerator
-
- amRules - Variable in class moa.classifiers.rules.core.Rule
-
- amRules - Variable in class moa.classifiers.rules.core.Rule.Builder
-
- amRules - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- amRules(AbstractAMRules) - Method in class moa.classifiers.rules.core.Rule.Builder
-
- AMRulesClassifierFunction - Interface in moa.classifiers.rules.functions
-
- AMRulesFunction - Interface in moa.classifiers.rules.multilabel.functions
-
- AMRulesLearner - Interface in moa.classifiers.rules.functions
-
- AMRulesMultiLabelClassifier - Class in moa.classifiers.rules.multilabel
-
Method for online multi-Label classification.
- AMRulesMultiLabelClassifier() - Constructor for class moa.classifiers.rules.multilabel.AMRulesMultiLabelClassifier
-
- AMRulesMultiLabelLearner - Class in moa.classifiers.rules.multilabel
-
Adaptive Model Rules for MultiLabel problems (AMRulesML), the streaming rule learning algorithm.
- AMRulesMultiLabelLearner() - Constructor for class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- AMRulesMultiLabelLearner(double) - Constructor for class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- AMRulesMultiLabelLearnerSemiSuper - Class in moa.classifiers.rules.multilabel
-
Semi-supervised method for online multi-target regression.
- AMRulesMultiLabelLearnerSemiSuper() - Constructor for class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- AMRulesMultiLabelLearnerSemiSuper(double) - Constructor for class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- AMRulesMultiTargetRegressor - Class in moa.classifiers.rules.multilabel
-
AMRules Algorithm for multitarget
splitCriterionOption- Split criterion used to assess the merit of a split
weightedVoteOption - Weighted vote type
learnerOption - Learner selection
errorMeasurerOption - Measure of error for deciding which learner should predict
changeDetector - Change selection
João Duarte, João Gama, Albert Bifet, Adaptive Model Rules From High-Speed Data Streams.
- AMRulesMultiTargetRegressor() - Constructor for class moa.classifiers.rules.multilabel.AMRulesMultiTargetRegressor
-
- AMRulesMultiTargetRegressor(double) - Constructor for class moa.classifiers.rules.multilabel.AMRulesMultiTargetRegressor
-
- AMRulesMultiTargetRegressorSemiSuper - Class in moa.classifiers.rules.multilabel
-
- AMRulesMultiTargetRegressorSemiSuper() - Constructor for class moa.classifiers.rules.multilabel.AMRulesMultiTargetRegressorSemiSuper
-
- AMRulesMultiTargetRegressorSemiSuper(double) - Constructor for class moa.classifiers.rules.multilabel.AMRulesMultiTargetRegressorSemiSuper
-
- AMRulesRegressor - Class in moa.classifiers.rules
-
- AMRulesRegressor() - Constructor for class moa.classifiers.rules.AMRulesRegressor
-
- AMRulesRegressorFunction - Interface in moa.classifiers.rules.functions
-
- AMRulesRegressorOld - Class in moa.classifiers.rules
-
- AMRulesRegressorOld() - Constructor for class moa.classifiers.rules.AMRulesRegressorOld
-
- AMRulesSplitCriterion - Interface in moa.classifiers.rules.core.splitcriteria
-
- AnadirtoFichero(String, String) - Static method in class moa.gui.experimentertab.statisticaltests.Fichero
-
- analizeTab - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- AnalyzeTab - Class in moa.gui.experimentertab
-
In this class are compared online learning algorithms on multiple datasets by
performing appropriate statistical tests.
- AnalyzeTab() - Constructor for class moa.gui.experimentertab.AnalyzeTab
-
Creates new form Analize
- AnomalinessRatioScore - Class in moa.classifiers.rules.core.anomalydetection
-
Score for anomaly detection
percentageAnomalousAttributesOption - Percentage of anomalous attributes.
- AnomalinessRatioScore() - Constructor for class moa.classifiers.rules.core.anomalydetection.AnomalinessRatioScore
-
- anomalyDetectionOption - Variable in class moa.classifiers.rules.RuleClassifier
-
- anomalyDetector - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- anomalyDetector - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- anomalyDetector - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- AnomalyDetector - Interface in moa.classifiers.rules.core.anomalydetection
-
Anomaly Detector interface to implement methods that detects change.
- anomalyDetector2 - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- anomalyNumInstThresholdOption - Variable in class moa.classifiers.rules.AbstractAMRules
-
- anomalyNumInstThresholdOption - Variable in class moa.classifiers.rules.RuleClassifier
-
- anomalyProbabilityThresholdOption - Variable in class moa.classifiers.rules.RuleClassifier
-
- anomalyScore - Variable in class moa.classifiers.rules.core.anomalydetection.AnomalinessRatioScore
-
- anomalyScore - Variable in class moa.classifiers.rules.core.anomalydetection.NoAnomalyDetection
-
- anomalyScore - Variable in class moa.classifiers.rules.core.anomalydetection.OddsRatioScore
-
- anomalyThresholdOption - Variable in class moa.classifiers.oneclass.HSTrees
-
- AnyOut - Class in moa.clusterers.outliers.AnyOut
-
- AnyOut() - Constructor for class moa.clusterers.outliers.AnyOut.AnyOut
-
- AnyOutCore - Class in moa.clusterers.outliers.AnyOut
-
- AnyOutCore() - Constructor for class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- appendIndent(StringBuilder, int) - Static method in class com.github.javacliparser.StringUtils
-
- appendIndent(StringBuilder, int) - Static method in class moa.core.StringUtils
-
- appendIndented(StringBuilder, int, String) - Static method in class com.github.javacliparser.StringUtils
-
- appendIndented(StringBuilder, int, String) - Static method in class moa.core.StringUtils
-
- appendNewline(StringBuilder) - Static method in class com.github.javacliparser.StringUtils
-
- appendNewline(StringBuilder) - Static method in class moa.core.StringUtils
-
- appendNewlineIndented(StringBuilder, int, String) - Static method in class com.github.javacliparser.StringUtils
-
- appendNewlineIndented(StringBuilder, int, String) - Static method in class moa.core.StringUtils
-
- applyChanges() - Method in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- applyChanges() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- applyChanges() - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- applyDrawDecay(float) - Method in class moa.gui.visualization.StreamPanel
-
- applyDrawDecay(float, boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- applyFilter(Filter) - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Passes the dataset through the filter that has been configured for use.
- applyState() - Method in class com.github.javacliparser.gui.ClassOptionEditComponent
-
- applyState() - Method in class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
- applyState() - Method in class com.github.javacliparser.gui.FileOptionEditComponent
-
- applyState() - Method in class com.github.javacliparser.gui.FlagOptionEditComponent
-
- applyState() - Method in class com.github.javacliparser.gui.FloatOptionEditComponent
-
- applyState() - Method in class com.github.javacliparser.gui.IntOptionEditComponent
-
- applyState() - Method in class com.github.javacliparser.gui.MultiChoiceOptionEditComponent
-
- applyState() - Method in interface com.github.javacliparser.gui.OptionEditComponent
-
This method applies the state
- applyState() - Method in class com.github.javacliparser.gui.StringOptionEditComponent
-
- applyState() - Method in class moa.gui.WEKAClassOptionEditComponent
-
- ApplyToCanvas(BufferedImage) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- ApproxSTORM - Class in moa.clusterers.outliers.Angiulli
-
- ApproxSTORM() - Constructor for class moa.clusterers.outliers.Angiulli.ApproxSTORM
-
- ApproxSTORM.ISBNodeAppr - Class in moa.clusterers.outliers.Angiulli
-
- ARFBaseLearner(int, ARFHoeffdingTree, BasicClassificationPerformanceEvaluator, long, boolean, boolean, ClassOption, ClassOption, boolean) - Constructor for class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- arff - Variable in class com.yahoo.labs.samoa.instances.Instances
-
The arff.
- ARFF_ATTRIBUTE - Static variable in class com.yahoo.labs.samoa.instances.Attribute
-
The keyword used to denote the start of an arff attribute declaration
- ARFF_ATTRIBUTE_DATE - Static variable in class com.yahoo.labs.samoa.instances.Attribute
-
The keyword used to denote a date attribute
- ARFF_ATTRIBUTE_INTEGER - Static variable in class com.yahoo.labs.samoa.instances.Attribute
-
A keyword used to denote a numeric attribute
- ARFF_ATTRIBUTE_NUMERIC - Static variable in class com.yahoo.labs.samoa.instances.Attribute
-
A keyword used to denote a numeric attribute
- ARFF_ATTRIBUTE_REAL - Static variable in class com.yahoo.labs.samoa.instances.Attribute
-
A keyword used to denote a numeric attribute
- ARFF_ATTRIBUTE_RELATIONAL - Static variable in class com.yahoo.labs.samoa.instances.Attribute
-
The keyword used to denote a relation-valued attribute
- ARFF_ATTRIBUTE_STRING - Static variable in class com.yahoo.labs.samoa.instances.Attribute
-
The keyword used to denote a string attribute
- ARFF_DATA - Static variable in class com.yahoo.labs.samoa.instances.Instances
-
The keyword used to denote the start of the arff data section
- ARFF_END_SUBRELATION - Static variable in class com.yahoo.labs.samoa.instances.Attribute
-
The keyword used to denote the end of the declaration of a subrelation
- ARFF_RELATION - Static variable in class com.yahoo.labs.samoa.instances.Instances
-
The keyword used to denote the start of an arff header
- arffFileOption - Variable in class moa.streams.ArffFileStream
-
- arffFileOption - Variable in class moa.streams.clustering.FileStream
-
- arffFileOption - Variable in class moa.streams.MultiTargetArffFileStream
-
- arffFileOption - Variable in class moa.tasks.WriteMultipleStreamsToARFF
-
- arffFileOption - Variable in class moa.tasks.WriteStreamToARFFFile
-
- ArffFileStream - Class in moa.streams
-
Stream reader of ARFF files.
- ArffFileStream() - Constructor for class moa.streams.ArffFileStream
-
- ArffFileStream(String, int) - Constructor for class moa.streams.ArffFileStream
-
- ARFFIMTDD - Class in moa.classifiers.trees
-
Implementation of ARFFIMTDD, an extension of FIMTDD to be used by AdaptiveRandomForestRegressor.
- ARFFIMTDD() - Constructor for class moa.classifiers.trees.ARFFIMTDD
-
- ARFFIMTDD.FIMTDDPerceptron - Class in moa.classifiers.trees
-
- ARFFIMTDD.InnerNode - Class in moa.classifiers.trees
-
- ARFFIMTDD.LeafNode - Class in moa.classifiers.trees
-
- ARFFIMTDD.Node - Class in moa.classifiers.trees
-
- ARFFIMTDD.SplitNode - Class in moa.classifiers.trees
-
- ARFFIMTDDBaseLearner(int, ARFFIMTDD, BasicRegressionPerformanceEvaluator, long, boolean, boolean, ClassOption, ClassOption, boolean) - Constructor for class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- ArffLoader - Class in com.yahoo.labs.samoa.instances
-
The Class ArffLoader.
- ArffLoader(Reader) - Constructor for class com.yahoo.labs.samoa.instances.ArffLoader
-
Instantiates a new arff loader.
- ArffLoader(Reader, int, int) - Constructor for class com.yahoo.labs.samoa.instances.ArffLoader
-
Instantiates a new arff loader.
- ArffLoader(Reader, Range) - Constructor for class com.yahoo.labs.samoa.instances.ArffLoader
-
Instantiates a new arff loader.
- ARFHoeffdingTree - Class in moa.classifiers.trees
-
Adaptive Random Forest Hoeffding Tree.
- ARFHoeffdingTree() - Constructor for class moa.classifiers.trees.ARFHoeffdingTree
-
- ARFHoeffdingTree.LearningNodeNB - Class in moa.classifiers.trees
-
- ARFHoeffdingTree.LearningNodeNBAdaptive - Class in moa.classifiers.trees
-
- ARFHoeffdingTree.RandomLearningNode - Class in moa.classifiers.trees
-
- array - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- array - Variable in class moa.core.DoubleVector
-
- arrayToString(Object) - Static method in class moa.core.Utils
-
Returns the given Array in a string representation.
- ASHoeffdingTree - Class in moa.classifiers.trees
-
Adaptive Size Hoeffding Tree used in Bagging using trees of different size.
- ASHoeffdingTree() - Constructor for class moa.classifiers.trees.ASHoeffdingTree
-
- AssetNegotiationGenerator - Class in moa.streams.generators
-
- AssetNegotiationGenerator() - Constructor for class moa.streams.generators.AssetNegotiationGenerator
-
- AssetNegotiationGenerator.ClassFunction - Interface in moa.streams.generators
-
- assignSubToCenters(KDTreeNode, Instances, int[], int[]) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Assigns instances of this node to center.
- attachUpdatable(Updatable) - Method in class moa.recommender.rc.data.AbstractRecommenderData
-
- attachUpdatable(Updatable) - Method in interface moa.recommender.rc.data.RecommenderData
-
- attemptInstallJavaLookAndFeel(String) - Static method in class moa.gui.LookAndFeel
-
Attempts to install the specified Look'n'Feel, but falls back on
cross-platform look if it fails.
- attemptInstallJideLookAndFeel(int) - Static method in class moa.gui.LookAndFeel
-
Attempts to install the specifoed JIDE style, but falls back on
cross-platform Java Look'n'Feel and JIDE style LookAndFeelFactory.VSNET_STYLE_WITHOUT_MENU
if it fails.
- attemptToSplit(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- attemptToSplit(Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNode
-
- attemptToSplit(ISOUPTree.LeafNode, ISOUPTree.SplitNode, int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- attemptToSplit(ARFFIMTDD.LeafNode, ARFFIMTDD.Node, int) - Method in class moa.classifiers.trees.ARFFIMTDD
-
- attemptToSplit(EFDT.ActiveLearningNode, EFDT.SplitNode, int) - Method in class moa.classifiers.trees.EFDT
-
- attemptToSplit(FIMTDD.LeafNode, FIMTDD.Node, int) - Method in class moa.classifiers.trees.FIMTDD
-
- attemptToSplit(FIMTDD.LeafNode, FIMTDD.Node, int) - Method in class moa.classifiers.trees.ORTO
-
- attemptToSplit(HoeffdingOptionTree.ActiveLearningNode, HoeffdingOptionTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- attemptToSplit(HoeffdingTree.ActiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTreeClassifLeaves
-
- attemptToSplit(HoeffdingTree.ActiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingTree
-
- attemptToSplit(HoeffdingTree.ActiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingTreeClassifLeaves
-
- attIndex - Variable in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
-
- attIndex - Variable in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
-
- attIndex - Variable in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
-
- attIndex - Variable in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- attIndex - Variable in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- attNoiseFractionOption - Variable in class moa.streams.filters.AddNoiseFilter
-
- attribute(int) - Method in class com.yahoo.labs.samoa.instances.AttributesInformation
-
Attribute.
- attribute(int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Attribute.
- attribute(int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Attribute.
- attribute(int) - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- attribute(int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Attribute.
- attribute(String) - Method in class com.yahoo.labs.samoa.instances.Instances
-
- Attribute - Class in com.yahoo.labs.samoa.instances
-
The Class Attribute.
- Attribute() - Constructor for class com.yahoo.labs.samoa.instances.Attribute
-
Instantiates a new attribute.
- Attribute(String) - Constructor for class com.yahoo.labs.samoa.instances.Attribute
-
Instantiates a new attribute.
- Attribute(String, String) - Constructor for class com.yahoo.labs.samoa.instances.Attribute
-
Instantiates a new attribute.
- Attribute(String, List<String>) - Constructor for class com.yahoo.labs.samoa.instances.Attribute
-
Instantiates a new attribute.
- AttributeClassObserver - Interface in moa.classifiers.core.attributeclassobservers
-
Interface for observing the class data distribution for an attribute.
- attributeDiferentiation - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- AttributeExpansionSuggestion - Class in moa.classifiers.rules.multilabel.core
-
Class for computing attribute split suggestions given a split test.
- AttributeExpansionSuggestion(Predicate, DoubleVector[][], double) - Constructor for class moa.classifiers.rules.multilabel.core.AttributeExpansionSuggestion
-
- attributeImportance - Variable in class moa.classifiers.rules.featureranking.BasicFeatureRanking
-
- attributeImportance - Variable in class moa.classifiers.rules.featureranking.MeritFeatureRanking
-
- attributeImportance - Variable in class moa.classifiers.rules.featureranking.WeightedMajorityFeatureRanking
-
- attributeIndicesTipText() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Returns the tip text for this property.
- attributeMissingValues - Variable in class moa.classifiers.rules.RuleClassification
-
- attributeObservers - Variable in class moa.classifiers.bayes.NaiveBayes
-
- attributeObservers - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- attributeObservers - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- attributeObservers - Variable in class moa.classifiers.rules.RuleClassifier
-
- attributeObservers - Variable in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- attributeObservers - Variable in class moa.classifiers.trees.DecisionStump
-
- attributeObservers - Variable in class moa.classifiers.trees.EFDT.ActiveLearningNode
-
- attributeObservers - Variable in class moa.classifiers.trees.EFDT.EFDTSplitNode
-
- attributeObservers - Variable in class moa.classifiers.trees.FIMTDD.LeafNode
-
- attributeObservers - Variable in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
-
- attributeObservers - Variable in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
-
- attributeObserversGauss - Variable in class moa.classifiers.rules.RuleClassifier
-
- attributes - Variable in class com.yahoo.labs.samoa.instances.AttributesInformation
-
The attribute information.
- attributes - Variable in class moa.clusterers.meta.Algorithm
-
- AttributeSelectionPanel - Class in moa.gui.featureanalysis
-
A sub panel in visualizeFeatures tab.
- AttributeSelectionPanel() - Constructor for class moa.gui.featureanalysis.AttributeSelectionPanel
-
Creates the attribute selection panel with no initial instances.
- AttributeSelectionPanel(boolean, boolean, boolean, boolean) - Constructor for class moa.gui.featureanalysis.AttributeSelectionPanel
-
Creates the attribute selection panel with no initial instances.
- attributesInformation - Variable in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- AttributesInformation - Class in com.yahoo.labs.samoa.instances
-
Class for storing the information of the attributes.
- AttributesInformation() - Constructor for class com.yahoo.labs.samoa.instances.AttributesInformation
-
- AttributesInformation(Attribute[], int) - Constructor for class com.yahoo.labs.samoa.instances.AttributesInformation
-
- AttributesInformation(Attribute[], int[], int) - Constructor for class com.yahoo.labs.samoa.instances.AttributesInformation
-
- AttributesInformation(AttributesInformation) - Constructor for class com.yahoo.labs.samoa.instances.AttributesInformation
-
- AttributesInformation(List<Attribute>, int) - Constructor for class com.yahoo.labs.samoa.instances.AttributesInformation
-
- attributesMask - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- attributesMask - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- attributesPercentage - Variable in class moa.classifiers.rules.AbstractAMRules
-
- attributesPercentage - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- attributesPercentage - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- attributesPercentage - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- AttributeSplitSuggestion - Class in moa.classifiers.core
-
Class for computing attribute split suggestions given a split test.
- AttributeSplitSuggestion(InstanceConditionalTest, double[][], double) - Constructor for class moa.classifiers.core.AttributeSplitSuggestion
-
- attributesProbability - Variable in class moa.classifiers.rules.RuleClassification
-
- attributeStatistics - Variable in class moa.classifiers.rules.RuleClassification
-
- AttributeStatisticsObserver - Interface in moa.classifiers.rules.multilabel.attributeclassobservers
-
Interface for observing the statistics for an attribute.
- attributeStatisticsSupervised - Variable in class moa.classifiers.rules.RuleClassification
-
- AttributeSummaryPanel - Class in moa.gui.featureanalysis
-
This panel displays summary statistics about an attribute: name, type
number/% of missing/unique values, number of distinct values.
- AttributeSummaryPanel() - Constructor for class moa.gui.featureanalysis.AttributeSummaryPanel
-
Creates the instances panel with no initial instances.
- attributeValues - Variable in class com.yahoo.labs.samoa.instances.Attribute
-
The attribute values.
- attributeValues - Variable in class com.yahoo.labs.samoa.instances.DenseInstanceData
-
The attribute values.
- attributeValues - Variable in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
The attribute values.
- AttributeVisualizationPanel - Class in moa.gui.featureanalysis
-
Creates a panel that shows a visualization of an attribute in a dataset.
- AttributeVisualizationPanel() - Constructor for class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Constructor - If used then the class will not show the class selection
combo box.
- AttributeVisualizationPanel(boolean) - Constructor for class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Constructor.
- attValDistPerClass - Variable in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- attValDistPerClass - Variable in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
-
- attValDistPerClass - Variable in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
-
- attValObservers - Variable in class moa.streams.filters.AddNoiseFilter
-
- attValue - Variable in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
-
- attValue - Variable in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
-
- attValue - Variable in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- attValueDist - Variable in class moa.classifiers.trees.iadem.Iadem2.NominalVirtualNode
-
- AutoClassDiscovery - Class in moa.core
-
Class for discovering classes via reflection in the java class path.
- AutoClassDiscovery() - Constructor for class moa.core.AutoClassDiscovery
-
- Autoencoder - Class in moa.classifiers.oneclass
-
Implements an autoencoder: a neural network that attempts to reconstruct the input.
- Autoencoder() - Constructor for class moa.classifiers.oneclass.Autoencoder
-
- AutoExpandVector<T> - Class in moa.core
-
Vector with the capability of automatic expansion.
- AutoExpandVector() - Constructor for class moa.core.AutoExpandVector
-
- AutoExpandVector(int) - Constructor for class moa.core.AutoExpandVector
-
- autoFreqStrings - Static variable in class moa.gui.experimentertab.ExpPreviewPanel
-
- autoFreqStrings - Static variable in class moa.gui.PreviewPanel
-
- autoFreqTimeSecs - Static variable in class moa.gui.experimentertab.ExpPreviewPanel
-
- autoFreqTimeSecs - Static variable in class moa.gui.PreviewPanel
-
- autoRefreshComboBox - Variable in class moa.gui.active.ALPreviewPanel
-
- autoRefreshComboBox - Variable in class moa.gui.experimentertab.ExpPreviewPanel
-
- autoRefreshComboBox - Variable in class moa.gui.PreviewPanel
-
- autoRefreshLabel - Variable in class moa.gui.active.ALPreviewPanel
-
- autoRefreshLabel - Variable in class moa.gui.experimentertab.ExpPreviewPanel
-
- autoRefreshLabel - Variable in class moa.gui.PreviewPanel
-
- autoRefreshTimer - Variable in class moa.gui.active.ALPreviewPanel
-
- autoRefreshTimer - Variable in class moa.gui.experimentertab.ExpPreviewPanel
-
- autoRefreshTimer - Variable in class moa.gui.PreviewPanel
-
- auxAttributes - Variable in class com.yahoo.labs.samoa.instances.ArffLoader
-
- AuxiliarMainTask - Class in moa.tasks
-
Abstract Auxiliar Main Task.
- AuxiliarMainTask() - Constructor for class moa.tasks.AuxiliarMainTask
-
- AuxiliarTabPanel - Class in moa.gui
-
This panel allows the user to select and configure a task, and run it.
- AuxiliarTabPanel() - Constructor for class moa.gui.AuxiliarTabPanel
-
- AuxiliarTaskManagerPanel - Class in moa.gui
-
This panel displays the running tasks.
- AuxiliarTaskManagerPanel() - Constructor for class moa.gui.AuxiliarTaskManagerPanel
-
- AuxiliarTaskManagerPanel.ProgressCellRenderer - Class in moa.gui
-
- AuxiliarTaskManagerPanel.TaskTableModel - Class in moa.gui
-
- AverageComparitionByHoeffdingCorollary(double, double, double) - Static method in class moa.classifiers.trees.iadem.IademCommonProcedures
-
- averageError - Variable in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- averageError - Variable in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- averageError - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- averageError - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- averageError - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- averageError - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- averageErrorToTargetMean - Variable in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- averageErrorToTargetMean - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- averageMeasurements(Measurement[][]) - Static method in class moa.core.Measurement
-
- averageTargetError - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- avgPerformance() - Method in class moa.gui.experimentertab.statisticaltests.StatisticalTest
-
Compute the average ranking of the algorithms.
- AWTInteractiveRenderer - Interface in moa.gui
-
- AWTRenderable - Interface in moa.gui
-
Interface representing a component that is renderable
- AWTRenderer - Interface in moa.gui
-
Interface representing a component to edit an option.
- axesPanel - Variable in class moa.gui.visualization.AbstractGraphCanvas
-
- c - Variable in class moa.classifiers.meta.PairedLearners
-
- c - Variable in class moa.streams.filters.RBFFilter
-
- c_max - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- c_min - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- cached(DistanceFunction<Data>) - Static method in class moa.clusterers.outliers.utils.mtree.DistanceFunctions
-
- cachedClassNames - Static variable in class moa.core.AutoClassDiscovery
-
- CachedInstancesStream - Class in moa.streams
-
Stream generator for representing a stream that is cached in memory.
- CachedInstancesStream(Instances) - Constructor for class moa.streams.CachedInstancesStream
-
- CacheShuffledStream - Class in moa.tasks
-
Task for storing and shuffling examples in memory.
- CacheShuffledStream() - Constructor for class moa.tasks.CacheShuffledStream
-
- cacheTestOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePeriodicHeldOutTest
-
- cacheTestOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
-
- calcByteSize() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- calcByteSize() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- calcByteSize() - Method in class moa.classifiers.trees.ARFFIMTDD
-
- calcByteSize() - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- calcByteSize() - Method in class moa.classifiers.trees.EFDT.ActiveLearningNode
-
- calcByteSize() - Method in class moa.classifiers.trees.EFDT
-
- calcByteSize() - Method in class moa.classifiers.trees.EFDT.Node
-
- calcByteSize() - Method in class moa.classifiers.trees.EFDT.SplitNode
-
- calcByteSize() - Method in class moa.classifiers.trees.FIMTDD
-
- calcByteSize() - Method in class moa.classifiers.trees.FIMTDD.Node
-
- calcByteSize() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- calcByteSize() - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
-
- calcByteSize() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- calcByteSize() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
-
- calcByteSize() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- calcByteSize() - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
-
- calcByteSize() - Method in class moa.classifiers.trees.HoeffdingTree
-
- calcByteSize() - Method in class moa.classifiers.trees.HoeffdingTree.Node
-
- calcByteSize() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.EFDT.Node
-
- calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.EFDT.SplitNode
-
- calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
-
- calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.HoeffdingTree.Node
-
- calcByteSizeIncludingSubtree() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- calcDistance(ClusKernel) - Method in class moa.clusterers.clustree.ClusKernel
-
Calculate the distance to this other cluster.
- calcDistance(ClusKernel) - Method in class moa.clusterers.clustree.Entry
-
Calculates the distance to the data in this entry.
- calcDistance(Entry) - Method in class moa.clusterers.clustree.Entry
-
Calculates the distance to the data in this entry of the data in the
given entry.
- calcGraph(int, int) - Method in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Recalculates the barplot or histogram to display, required usually when the
attribute is changed or the component is resized.
- calcKMeansCosts(double[]) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Calculates the k-means costs of the ClusteringFeature too a center.
- calcKMeansCosts(double[], double[]) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Calculates the k-means costs of the ClusteringFeature and a point too a
center.
- calcKMeansCosts(double[], ClusteringFeature) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Calculates the k-means costs of the ClusteringFeature and another
ClusteringFeature too a center.
- calcNodeCover(HoeffdingTree.SplitNode) - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTree
-
- calcNodeDecreaseImpurity(HoeffdingTree.SplitNode) - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTree
-
- calcR(int) - Method in class moa.clusterers.kmeanspm.BICO
-
Calculates the threshold at a specific level in the ClusteringFeature
tree.
- calcRSquared(int) - Method in class moa.clusterers.kmeanspm.BICO
-
Calculates the squared threshold at a specific level in the
ClusteringFeature tree.
- calculate(DATA, DATA) - Method in interface moa.clusterers.outliers.utils.mtree.DistanceFunction
-
- calculateAuc - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- calculateAUC - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator
-
- calculatePromise() - Method in class moa.classifiers.trees.EFDT.Node
-
- calculatePromise() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
-
- calculatePromise() - Method in class moa.classifiers.trees.HoeffdingTree.Node
-
- call() - Method in class moa.classifiers.core.statisticaltests.Cramer
-
- call() - Method in class moa.classifiers.core.statisticaltests.KNN
-
- call() - Method in class moa.classifiers.meta.AdaptiveRandomForest.TrainingRunnable
-
- call() - Method in class moa.clusterers.meta.EnsembleClustererAbstract.EnsembleRunnable
-
- cancelFlag - Variable in class moa.tasks.StandardTaskMonitor
-
- CANCELLED - moa.gui.experimentertab.ExpTaskThread.Status
-
- CANCELLED - moa.tasks.TaskThread.Status
-
- CANCELLING - moa.gui.experimentertab.ExpTaskThread.Status
-
- CANCELLING - moa.tasks.TaskThread.Status
-
- cancelSelectedTasks() - Method in class moa.gui.active.ALTaskManagerPanel
-
- cancelSelectedTasks() - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- cancelSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- cancelSelectedTasks() - Method in class moa.gui.experimentertab.TaskManagerTabPanel
-
Cancel task
- cancelSelectedTasks() - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- cancelSelectedTasks() - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- cancelSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
-
- cancelSelectedTasks() - Method in class moa.gui.TaskManagerPanel
-
- cancelTask() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- cancelTask() - Method in class moa.tasks.meta.ALTaskThread
-
- cancelTask() - Method in class moa.tasks.TaskThread
-
- cancelTaskButton - Variable in class moa.gui.active.ALTaskManagerPanel
-
- cancelTaskButton - Variable in class moa.gui.AuxiliarTaskManagerPanel
-
- cancelTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- cancelTaskButton - Variable in class moa.gui.MultiLabelTaskManagerPanel
-
- cancelTaskButton - Variable in class moa.gui.MultiTargetTaskManagerPanel
-
- cancelTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
-
- cancelTaskButton - Variable in class moa.gui.TaskManagerPanel
-
- canCreateSubtree() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- canCreateSubtree() - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- candidate - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Candidate classifier.
- candidate - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Candidate classifier.
- candidateClassifier - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- candidateEnsemble - Variable in class moa.clusterers.meta.EnsembleClustererAbstract
-
- candidateIsFullOwner(KDTreeNode, Instance, Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns true if candidate is a full owner in respect to a competitor.
- CantellisInequality - Class in moa.classifiers.rules.core.anomalydetection.probabilityfunctions
-
Returns the probability for anomaly detection according to a Cantelli inequality
mean- mean of a data variable
sd- standard deviation of a data variable
value- current value of the variable
- CantellisInequality() - Constructor for class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.CantellisInequality
-
- CANVAS - moa.gui.experimentertab.PlotTab.Terminal
-
- CANVAS - moa.tasks.Plot.Terminal
-
- Capabilities - Class in moa.capabilities
-
Container class representing the set of capabilities an object
has.
- Capabilities() - Constructor for class moa.capabilities.Capabilities
-
Creates a capabilities object with no capabilities.
- Capabilities(Capability...) - Constructor for class moa.capabilities.Capabilities
-
Creates a capabilities object with the given capabilities.
- CapabilitiesHandler - Interface in moa.capabilities
-
Interface marking classes as being able to specify the capabilities
they can handle.
- Capability - Enum in moa.capabilities
-
Class enumerating the different possible capabilities of objects in
MOA.
- CapabilityRequirement - Class in moa.capabilities
-
Represents a requirement that a set of capabilities must meet.
- CapabilityRequirement(Predicate<Capabilities>) - Constructor for class moa.capabilities.CapabilityRequirement
-
Creates a capabilities requirement with the given predicate
as its method of checking if the requirement is met.
- caseAnomaly - Variable in class moa.classifiers.rules.RuleClassifier
-
- caseAnomalySupervised - Variable in class moa.classifiers.rules.RuleClassifier
-
- cast(Object) - Static method in class moa.core.Utils
-
Casting an object without "unchecked" compile-time warnings.
- CategoricalParameter - Class in moa.clusterers.meta
-
- CategoricalParameter(CategoricalParameter) - Constructor for class moa.clusterers.meta.CategoricalParameter
-
- CategoricalParameter(ParameterConfiguration) - Constructor for class moa.clusterers.meta.CategoricalParameter
-
- causeOfSplit - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- CDF_Normal - Class in moa.gui.experimentertab.statisticaltests
-
This class contains routines to calculate the
normal cumulative distribution function (CDF) and
its inverse.
- CDF_Normal() - Constructor for class moa.gui.experimentertab.statisticaltests.CDF_Normal
-
- cds - Variable in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
-
- CDTaskManagerPanel - Class in moa.gui.conceptdrift
-
This panel displays the running tasks.
- CDTaskManagerPanel() - Constructor for class moa.gui.conceptdrift.CDTaskManagerPanel
-
- CDTaskManagerPanel.ProgressCellRenderer - Class in moa.gui.conceptdrift
-
- CDTaskManagerPanel.TaskTableModel - Class in moa.gui.conceptdrift
-
- cellType() - Method in class moa.tasks.ipynb.CodeCellBuilder
-
- cellType() - Method in class moa.tasks.ipynb.MarkDownCellBuilder
-
- cellType() - Method in class moa.tasks.ipynb.NotebookCellBuilder
-
Gets the cell-type string of this type of cell.
- cellType() - Method in class moa.tasks.ipynb.RawCellBuilder
-
- center() - Method in class moa.cluster.Miniball
-
Return the center of the Miniball
- CENTER_INSIDE - moa.tasks.Plot.LegendLocation
-
- CENTER_OUTSIDE - moa.tasks.Plot.LegendLocation
-
- centerInstances(Instances, int[], double) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Assigns instances to centers using KDTree.
- centre - Variable in class moa.streams.generators.RandomRBFGenerator.Centroid
-
- centresStreamingCoreset - Variable in class moa.clusterers.streamkm.StreamKM
-
- Centroid() - Constructor for class moa.streams.generators.RandomRBFGenerator.Centroid
-
- centroids - Variable in class moa.streams.generators.RandomRBFGenerator
-
- centroidWeights - Variable in class moa.streams.generators.RandomRBFGenerator
-
- cEstimacion - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- CFCluster - Class in moa.cluster
-
- CFCluster(double[], int) - Constructor for class moa.cluster.CFCluster
-
- CFCluster(int) - Constructor for class moa.cluster.CFCluster
-
- CFCluster(Instance, int) - Constructor for class moa.cluster.CFCluster
-
Instantiates an empty kernel with the given dimensionality.
- CFCluster(CFCluster) - Constructor for class moa.cluster.CFCluster
-
- change - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- changeChildren(Iadem2.Node, Iadem2.Node) - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- changeCluster(ClusterEvent) - Method in class moa.gui.BatchCmd
-
- changeCluster(ClusterEvent) - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- changeCluster(ClusterEvent) - Method in class moa.gui.visualization.RunVisualizer
-
- changeCluster(ClusterEvent) - Method in interface moa.streams.clustering.ClusterEventListener
-
- changeDetected - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- changeDetected - Variable in class moa.classifiers.meta.PairedLearners
-
- ChangeDetectedMessage - Class in moa.classifiers.rules.featureranking.messages
-
- ChangeDetectedMessage() - Constructor for class moa.classifiers.rules.featureranking.messages.ChangeDetectedMessage
-
- changeDetection - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- changeDetection - Variable in class moa.classifiers.rules.core.Rule.Builder
-
- changeDetection - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- changeDetection - Variable in class moa.classifiers.trees.ARFFIMTDD.Node
-
- changeDetection - Variable in class moa.classifiers.trees.FIMTDD.Node
-
- changeDetection(boolean) - Method in class moa.classifiers.rules.core.Rule.Builder
-
- ChangeDetectionMeasures - Class in moa.evaluation
-
- ChangeDetectionMeasures() - Constructor for class moa.evaluation.ChangeDetectionMeasures
-
- changeDetector - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- changeDetector - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- changeDetector - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- ChangeDetector - Interface in moa.classifiers.core.driftdetection
-
Change Detector interface to implement methods that detects change.
- ChangeDetectorLearner - Class in moa.learners
-
Class for detecting concept drift and to be used as a learner.
- ChangeDetectorLearner() - Constructor for class moa.learners.ChangeDetectorLearner
-
- changeDetectors - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- changeDetectorsOption - Variable in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
-
- changeDriftOption - Variable in class moa.streams.generators.cd.GradualChangeGenerator
-
- changeFreqWords(int) - Method in class moa.streams.generators.TextGenerator
-
- changeListeners - Variable in class com.github.javacliparser.gui.ClassOptionEditComponent
-
listeners that listen to changes to the chosen option.
- changeListeners - Variable in class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
listeners that listen to changes to the chosen option.
- changePolarity(int) - Method in class moa.streams.generators.TextGenerator
-
- CharacteristicVector - Class in moa.clusterers.dstream
-
The Characteristic Vector of a density grid is defined in
Definition 3.2 of Chen and Tu 2007 as:
The characteristic vector of a grid g is a tuple (tg,tm,D, label,status),
where tg is the last time when g is updated, tm is the last time when g
is removed from grid list as a sporadic grid (if ever), D is the grid
density at the last update, label is the class label of the grid, and
status = {SPORADIC, NORMAL} is a label used for removing sporadic grids.
- CharacteristicVector(int, int, double, int, boolean, double, double) - Constructor for class moa.clusterers.dstream.CharacteristicVector
-
- ChebyshevInequality - Class in moa.classifiers.rules.core.anomalydetection.probabilityfunctions
-
Returns the probability for anomaly detection according to a Chebyshev inequality
mean- mean of a data variable
sd- standard deviation of a data variable
value- current value of the variable
- ChebyshevInequality() - Constructor for class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.ChebyshevInequality
-
- check_in(double[]) - Method in class moa.cluster.Miniball
-
Adds a point to the list.
Skip action on null parameter.
- checkBestAttrib(double, AutoExpandVector<AttributeClassObserver>, DoubleVector) - Method in class moa.classifiers.rules.RuleClassifier
-
- checkForRemainingOptions(String[]) - Static method in class moa.core.Utils
-
Checks if the given array contains any non-empty options.
- checkForSplit() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.LeafNode
-
- checkForSplit(ARFFIMTDD) - Method in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- checkForSplit(FIMTDD) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
-
- checkHomogeneity(SEEDChangeDetector.SEEDBlock) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- checkMissing(Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Checks if there is any missing value in the given
instance.
- checkMissing(Instances) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Checks if there is any instance with missing values.
- checkRoot() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- checkRoot() - Method in class moa.classifiers.trees.ARFFIMTDD
-
- checkRoot() - Method in class moa.classifiers.trees.FIMTDD
-
- children - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- children - Variable in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- children - Variable in class moa.classifiers.trees.EFDT.SplitNode
-
- children - Variable in class moa.classifiers.trees.FIMTDD.InnerNode
-
- children - Variable in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- children - Variable in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- children - Variable in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- children - Variable in class moa.streams.generators.RandomTreeGenerator.Node
-
- chiSquaredProbability(double, double) - Static method in class moa.core.Statistics
-
Returns chi-squared probability for given value and degrees
of freedom.
- chooseRandomIndexBasedOnWeights(double[], Random) - Static method in class moa.core.MiscUtils
-
- chosenObject - Variable in class moa.gui.ClassOptionSelectionPanel
-
- chosenObject - Variable in class moa.gui.ClassOptionWithNamesSelectionPanel
-
- chosenObjectEditor - Variable in class moa.gui.ClassOptionSelectionPanel
-
- chosenObjectEditor - Variable in class moa.gui.ClassOptionWithNamesSelectionPanel
-
- chosenOptionIndex - Variable in class com.github.javacliparser.MultiChoiceOption
-
- chunkSize - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- chunkSizeOption - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Chunk size.
- chunkSizeOption - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Chunk size.
- chunkSizeOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedChunks
-
Allow to define the training/testing chunk size.
- chunkSizeOption - Variable in class moa.tasks.EvaluateInterleavedChunks
-
Allow to define the training/testing chunk size.
- cindex(Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.StatisticalCollection
-
- CLASS_LIST - Static variable in class moa.core.AutoClassDiscovery
-
- classAttribute() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Class attribute.
- classAttribute() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Class attribute.
- classAttribute() - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- classAttribute() - Method in class com.yahoo.labs.samoa.instances.Instances
-
Class attribute.
- classChoiceBox - Variable in class moa.gui.ClassOptionSelectionPanel
-
- classChoiceBox - Variable in class moa.gui.ClassOptionWithNamesSelectionPanel
-
- classChoiceChanged(Object) - Method in class moa.gui.ClassOptionSelectionPanel
-
- classChoiceChanged(Object) - Method in class moa.gui.ClassOptionWithNamesSelectionPanel
-
- classCountsLeft - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
-
- classCountsRight - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
-
- classDist - Variable in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- classDist - Variable in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- classDistributionAtTimeOfCreation - Variable in class moa.classifiers.trees.EFDT.Node
-
- classDistributions - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Class distributions.
- classDistributions - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- classDistributions - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Class distributions.
- classFunction - Variable in class moa.streams.generators.AssetNegotiationGenerator
-
- CLASSIFICATION - moa.gui.experimentertab.ExpPreviewPanel.TypePanel
-
- CLASSIFICATION - moa.gui.PreviewPanel.TypePanel
-
- classificationFunctions - Static variable in class moa.streams.generators.AgrawalGenerator
-
- classificationFunctions - Static variable in class moa.streams.generators.MixedGenerator
-
- classificationFunctions - Static variable in class moa.streams.generators.SEAGenerator
-
- classificationFunctions - Static variable in class moa.streams.generators.SineGenerator
-
- classificationFunctions - Static variable in class moa.streams.generators.STAGGERGenerator
-
- ClassificationMainTask - Class in moa.tasks
-
Abstract Classification Main Task.
- ClassificationMainTask() - Constructor for class moa.tasks.ClassificationMainTask
-
- ClassificationMeasureCollection - Interface in moa.evaluation
-
Classification Measure Collection interface that it is used to not appear in clustering
- ClassificationPerformanceEvaluator - Interface in moa.evaluation
-
- ClassificationTabPanel - Class in moa.gui
-
This panel allows the user to select and configure a task, and run it.
- ClassificationTabPanel() - Constructor for class moa.gui.ClassificationTabPanel
-
- classifier - Variable in class moa.classifiers.active.ALRandom
-
- classifier - Variable in class moa.classifiers.active.ALUncertainty
-
- classifier - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- classifier - Variable in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- classifier - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- classifier - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- classifier - Variable in class moa.classifiers.meta.WEKAClassifier
-
- classifier - Variable in class moa.classifiers.multilabel.MEKAClassifier
-
- classifier - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTreeClassifLeaves.LearningNodeHATClassifier
-
- classifier - Variable in class moa.classifiers.trees.HoeffdingTreeClassifLeaves.LearningNodeClassifier
-
- Classifier - Interface in moa.classifiers
-
Classifier interface for incremental classification models.
- classifierParameterOption - Variable in class moa.tasks.RunTasks
-
- classifierPurposeString - Static variable in class moa.clusterers.CobWeb
-
- classifierRandom - Variable in class moa.classifiers.AbstractClassifier
-
Random Generator used in randomizable learners
- classifierRandom - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- classifierRandom - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- classifiersSizeOption - Variable in class moa.classifiers.meta.RCD
-
- classifierTipText() - Method in class weka.classifiers.meta.MOA
-
Returns the tooltip displayed in the GUI.
- ClassifierWithFeatureImportance - Class in moa.learners.featureanalysis
-
Classifier with Feature Importance
- ClassifierWithFeatureImportance() - Constructor for class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- ClassifierWithMemory(Classifier, int) - Constructor for class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble.ClassifierWithMemory
-
- classifyInstance(RandomTreeGenerator.Node, double[]) - Method in class moa.streams.generators.RandomTreeGenerator
-
- classIndex - Variable in class com.yahoo.labs.samoa.instances.InstanceInformation
-
The class index.
- classIndex() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Class index.
- classIndex() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Class index.
- classIndex() - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- classIndex() - Method in class com.yahoo.labs.samoa.instances.Instances
-
Class index.
- classIndexOption - Variable in class moa.streams.ArffFileStream
-
- classIndexOption - Variable in class moa.streams.clustering.FileStream
-
- classIndexOption - Variable in class moa.streams.clustering.SimpleCSVStream
-
- classIsMissing() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Class is missing.
- classIsMissing() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Class is missing.
- classLabel - Variable in class moa.streams.generators.RandomRBFGenerator.Centroid
-
- classLabel - Variable in class moa.streams.generators.RandomTreeGenerator.Node
-
- classNoiseFractionOption - Variable in class moa.streams.filters.AddNoiseFilter
-
- ClassOption - Class in com.github.javacliparser
-
Class option.
- ClassOption - Class in moa.options
-
Class option.
- ClassOption(String, char, String, Class<?>, String) - Constructor for class com.github.javacliparser.ClassOption
-
- ClassOption(String, char, String, Class<?>, String) - Constructor for class moa.options.ClassOption
-
- ClassOption(String, char, String, Class<?>, String, String) - Constructor for class com.github.javacliparser.ClassOption
-
- ClassOption(String, char, String, Class<?>, String, String) - Constructor for class moa.options.ClassOption
-
- ClassOptionEditComponent - Class in com.github.javacliparser.gui
-
An OptionEditComponent that lets the user edit a class option.
- ClassOptionEditComponent(Option) - Constructor for class com.github.javacliparser.gui.ClassOptionEditComponent
-
- classOptionNamesToPreparedObjects - Variable in class com.github.javacliparser.JavaCLIParser
-
Dictionary with option texts and objects
- ClassOptionSelectionPanel - Class in moa.gui
-
Creates a panel that displays the classes available, letting the user select
a class.
- ClassOptionSelectionPanel(Class<?>, String, String) - Constructor for class moa.gui.ClassOptionSelectionPanel
-
- ClassOptionWithListenerOption - Class in moa.options
-
ClassOption that can be given a ChangeListener.
- ClassOptionWithListenerOption(String, char, String, Class<?>, String) - Constructor for class moa.options.ClassOptionWithListenerOption
-
- ClassOptionWithListenerOption(String, char, String, Class<?>, String, String) - Constructor for class moa.options.ClassOptionWithListenerOption
-
- ClassOptionWithListenerOption(String, char, String, Class<?>, String, String, ChangeListener) - Constructor for class moa.options.ClassOptionWithListenerOption
-
- ClassOptionWithListenerOption(String, char, String, Class<?>, String, ChangeListener) - Constructor for class moa.options.ClassOptionWithListenerOption
-
- ClassOptionWithListenerOptionEditComponent - Class in moa.gui
-
- ClassOptionWithListenerOptionEditComponent(Option) - Constructor for class moa.gui.ClassOptionWithListenerOptionEditComponent
-
- ClassOptionWithNames - Class in moa.options
-
- ClassOptionWithNames(String, char, String, Class<?>, String, String[]) - Constructor for class moa.options.ClassOptionWithNames
-
- ClassOptionWithNames(String, char, String, Class<?>, String, String, String[]) - Constructor for class moa.options.ClassOptionWithNames
-
- ClassOptionWithNamesEditComponent - Class in com.github.javacliparser.gui
-
- ClassOptionWithNamesEditComponent(ClassOptionWithNames) - Constructor for class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
- ClassOptionWithNamesSelectionPanel - Class in moa.gui
-
- ClassOptionWithNamesSelectionPanel(Class<?>, String, String, String[]) - Constructor for class moa.gui.ClassOptionWithNamesSelectionPanel
-
- classRatioOption - Variable in class moa.streams.ImbalancedStream
-
- classToCLIString(Class<?>, Class<?>) - Static method in class com.github.javacliparser.AbstractClassOption
-
Gets the command line interface text of the class.
- classToCLIString(Class<?>, Class<?>) - Static method in class moa.options.AbstractClassOption
-
Gets the command line interface text of the class.
- classTwitterGenerator - Variable in class moa.streams.generators.TextGenerator
-
- classValue() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Class value.
- classValue() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Class value.
- classValue(int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Gets the value of an output attribute.
- classValue(int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- classValueDist - Variable in class moa.classifiers.trees.iadem.Iadem2.Node
-
- classValues - Static variable in class moa.streams.generators.AssetNegotiationGenerator
-
- classValues(List<? extends Instance>) - Static method in class moa.cluster.Clustering
-
- classWeights - Variable in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver.Bin
-
- classWeights - Variable in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver.Bin
-
- clean(int) - Method in class moa.evaluation.MeasureCollection
-
- cleanTables() - Method in class moa.gui.experimentertab.AnalyzeTab
-
Tables of algorithms and datasets are cleaned.
- cleanTables() - Method in class moa.gui.experimentertab.PlotTab
-
Clean the tables
- cleanTables() - Method in class moa.gui.experimentertab.SummaryTab
-
Clean the tables
- cleanTables() - Method in class moa.gui.experimentertab.TaskManagerTabPanel
-
Clean the tables
- cleanUpKMeans(Clustering, ArrayList<CFCluster>) - Static method in class moa.clusterers.clustream.WithKmeans
-
Rearrange the k-means result into a set of CFClusters, cleaning up the redundancies.
- clear() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- clear() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Reservoir
-
- clear() - Method in class moa.cluster.Miniball
-
Method clear: clears the ArrayList of the selection points.
Use it for starting a new selection list to calculate Bounding Sphere on
or to clear memory references to the list of objects.
Always use at the end of a Miniball use if you want to reuse later the Miniball object
- clear() - Method in class moa.clusterers.clustree.ClusKernel
-
Remove all points from this cluster.
- clear() - Method in class moa.clusterers.clustree.Entry
-
Clear the Entry.
- clear() - Method in class moa.clusterers.clustree.Node
-
Clear this Node, which means that the noiseBuffer is cleared, that
shallowClear is called upon all the entries of the node,
that the split counter is set to zero and the node is set to not be a
fake root.
- clear() - Method in class moa.clusterers.kmeanspm.CuckooHashing
-
Removes all of the elements from this hash table.
- clear() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
- clear() - Method in class moa.core.AutoExpandVector
-
- clear() - Method in class moa.recommender.rc.data.AbstractRecommenderData
-
- clear() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- clear() - Method in interface moa.recommender.rc.data.RecommenderData
-
- clearChildren() - Method in class moa.clusterers.kmeanspm.ClusteringTreeHeadNode
-
- clearChildren() - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Removes all children nodes.
- clearEvents() - Method in class moa.gui.visualization.StreamOutlierPanel
-
- clearOtherOutputs() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- clearPoints() - Method in class moa.gui.visualization.StreamOutlierPanel
-
- cliChar - Variable in class com.github.javacliparser.AbstractOption
-
Command line interface text of this option.
- clipToInsideHrect(KDTreeNode, Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Finds the closest point in the hyper rectangle to a given point.
- cliStringToDouble(String) - Static method in class com.github.javacliparser.FloatOption
-
- cliStringToInt(String) - Static method in class com.github.javacliparser.IntOption
-
- cliStringToObject(String, Class<?>, Option[]) - Static method in class com.github.javacliparser.ClassOption
-
- cliStringToObject(String, Class<?>, Option[]) - Static method in class moa.options.ClassOption
-
- cliStringToObject(String, Class<?>, Option[]) - Static method in class moa.options.ClassOptionWithNames
-
- cliStringToObject(String, Class<?>, Option[]) - Static method in class moa.options.WEKAClassOption
-
- cliStringToOptionArray(String, char, Option) - Static method in class com.github.javacliparser.ListOption
-
- clone() - Method in class moa.clusterers.streamkm.Point
-
- clone() - Method in class moa.gui.experimentertab.Measure
-
- clOption - Variable in class moa.clusterers.dstream.Dstream
-
- close() - Method in class moa.recommender.rc.data.AbstractRecommenderData
-
- close() - Method in interface moa.recommender.rc.data.RecommenderData
-
- closeDialog() - Method in class weka.gui.MOAClassOptionEditor
-
Closes the dialog.
- closestPoint(Instance, Instances, int[]) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance
-
Returns the index of the closest point to the current instance.
- ClusKernel - Class in moa.clusterers.clustree
-
Representation of an Entry in the tree
- ClusKernel(double[], int) - Constructor for class moa.clusterers.clustree.ClusKernel
-
A constructor that makes a Kernel which just represents the given point.
- ClusKernel(int) - Constructor for class moa.clusterers.clustree.ClusKernel
-
Constructor of the Cluster.
- ClusKernel(ClusKernel) - Constructor for class moa.clusterers.clustree.ClusKernel
-
Instantiates a copy of the given cluster.
- Cluster - Class in moa.cluster
-
- Cluster() - Constructor for class moa.cluster.Cluster
-
- clusterAddOption - Variable in class moa.clusterers.ClusterGenerator
-
- clusterer - Variable in class moa.clusterers.meta.Algorithm
-
- Clusterer - Interface in moa.clusterers
-
- clustererRandom - Variable in class moa.clusterers.AbstractClusterer
-
- clustererRandom - Variable in class moa.clusterers.streamkm.BucketManager
-
- clustererRandom - Variable in class moa.clusterers.streamkm.StreamKM
-
- ClusterEvent - Class in moa.streams.clustering
-
- ClusterEvent(Object, long, String, String) - Constructor for class moa.streams.clustering.ClusterEvent
-
- ClusterEventListener - Interface in moa.streams.clustering
-
- clusterEvents - Variable in class moa.streams.ArffFileStream
-
- clusterEvents - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- ClusterGenerator - Class in moa.clusterers
-
- ClusterGenerator() - Constructor for class moa.clusterers.ClusterGenerator
-
- clustering - Variable in class moa.clusterers.AbstractClusterer
-
- Clustering - Class in moa.cluster
-
- Clustering() - Constructor for class moa.cluster.Clustering
-
- Clustering(ArrayList<DataPoint>, double, int) - Constructor for class moa.cluster.Clustering
-
- Clustering(List<? extends Instance>) - Constructor for class moa.cluster.Clustering
-
- Clustering(Cluster[]) - Constructor for class moa.cluster.Clustering
-
- Clustering(AutoExpandVector<Cluster>) - Constructor for class moa.cluster.Clustering
-
- ClusteringAlgoPanel - Class in moa.gui.clustertab
-
- ClusteringAlgoPanel() - Constructor for class moa.gui.clustertab.ClusteringAlgoPanel
-
- ClusteringEvalPanel - Class in moa.gui.clustertab
-
- ClusteringEvalPanel() - Constructor for class moa.gui.clustertab.ClusteringEvalPanel
-
Creates new form ClusteringEvalPanel
- ClusteringFeature - Class in moa.clusterers.kmeanspm
-
Provides a ClusteringFeature.
- ClusteringFeature(double[], double) - Constructor for class moa.clusterers.kmeanspm.ClusteringFeature
-
Creates a ClusteringFeature.
- ClusteringFeature(double[], int, double[], double, double) - Constructor for class moa.clusterers.kmeanspm.ClusteringFeature
-
Creates a ClusteringFeature.
- ClusteringSetupTab - Class in moa.gui.clustertab
-
- ClusteringSetupTab() - Constructor for class moa.gui.clustertab.ClusteringSetupTab
-
Creates new form ClusteringSetupTab
- ClusteringStream - Class in moa.streams.clustering
-
- ClusteringStream() - Constructor for class moa.streams.clustering.ClusteringStream
-
- ClusteringTabPanel - Class in moa.gui.clustertab
-
- ClusteringTabPanel() - Constructor for class moa.gui.clustertab.ClusteringTabPanel
-
Creates new form ClusterTab
- ClusteringTreeHeadNode - Class in moa.clusterers.kmeanspm
-
Provides a ClusteringTreeNode with an extended nearest neighbor search in the
root.
- ClusteringTreeHeadNode(double[], ClusteringFeature, int, int, int, Random) - Constructor for class moa.clusterers.kmeanspm.ClusteringTreeHeadNode
-
Creates a ClusteringTreeNode with an extended nearest neighbor search in
the root.
- ClusteringTreeNode - Class in moa.clusterers.kmeanspm
-
Provides a tree of ClusterFeatures.
- ClusteringTreeNode(double[], ClusteringFeature) - Constructor for class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Creates a tree node for a ClusterFeature.
- ClusteringVisualEvalPanel - Class in moa.gui.clustertab
-
- ClusteringVisualEvalPanel() - Constructor for class moa.gui.clustertab.ClusteringVisualEvalPanel
-
Creates new form ClusteringEvalPanel
- ClusteringVisualTab - Class in moa.gui.clustertab
-
- ClusteringVisualTab() - Constructor for class moa.gui.clustertab.ClusteringVisualTab
-
Creates new form ClusteringVisualTab
- ClusterPanel - Class in moa.gui.visualization
-
- ClusterPanel(SphereCluster, Color, StreamPanel) - Constructor for class moa.gui.visualization.ClusterPanel
-
Creates new form ObjectPanel
- clusterRemoveOption - Variable in class moa.clusterers.ClusterGenerator
-
- Clustream - Class in moa.clusterers.clustream
-
Citation: CluStream: Charu C.
- Clustream() - Constructor for class moa.clusterers.clustream.Clustream
-
- ClustreamKernel - Class in moa.clusterers.clustream
-
- ClustreamKernel(Instance, int, long, double, int) - Constructor for class moa.clusterers.clustream.ClustreamKernel
-
- ClustreamKernel(ClustreamKernel, double, int) - Constructor for class moa.clusterers.clustream.ClustreamKernel
-
- ClusTree - Class in moa.clusterers.clustree
-
Citation: ClusTree: Philipp Kranen, Ira Assent, Corinna Baldauf, Thomas Seidl:
The ClusTree: indexing micro-clusters for anytime stream mining.
- ClusTree() - Constructor for class moa.clusterers.clustree.ClusTree
-
- CMM - Class in moa.evaluation
-
- CMM() - Constructor for class moa.evaluation.CMM
-
- CMM_GTAnalysis - Class in moa.evaluation
-
- CMM_GTAnalysis(Clustering, ArrayList<DataPoint>, boolean) - Constructor for class moa.evaluation.CMM_GTAnalysis
-
- CMM_GTAnalysis.CMMPoint - Class in moa.evaluation
-
Wrapper class for data points to store CMM relevant attributes
- CMM_GTAnalysis.GTCluster - Class in moa.evaluation
-
Main class to model the new clusters that will be the output of the cluster analysis
- cmmOption - Variable in class moa.tasks.EvaluateClustering
-
- cmmOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- CMMPoint(DataPoint, int) - Constructor for class moa.evaluation.CMM_GTAnalysis.CMMPoint
-
- cmOption - Variable in class moa.clusterers.dstream.Dstream
-
- CobWeb - Class in moa.clusterers
-
Class implementing the Cobweb and Classit clustering algorithms.
- CobWeb() - Constructor for class moa.clusterers.CobWeb
-
- CodeCellBuilder - Class in moa.tasks.ipynb
-
Implement a code cell
- col - Variable in class moa.gui.visualization.ClusterPanel
-
- col - Variable in class moa.gui.visualization.OutlierPanel
-
- col - Variable in class moa.gui.visualization.PointPanel
-
- ColorArray - Class in moa.clusterers.macro
-
- ColorArray() - Constructor for class moa.clusterers.macro.ColorArray
-
- colorCoding - Variable in class moa.tasks.meta.MetaMainTask
-
- ColorGenerator - Interface in moa.gui.colorGenerator
-
This interface specifies the generateColors method for classes
which generate colors according different strategies such that
those colors can be distinguished easily.
- ColorObject - Class in moa.clusterers.macro
-
- ColorObject(String, Color) - Constructor for class moa.clusterers.macro.ColorObject
-
- colors - Variable in class moa.gui.visualization.AbstractGraphPlot
-
- colorValues - Static variable in class moa.streams.generators.AssetNegotiationGenerator
-
- colour - Variable in class moa.gui.LineGraphViewPanel.PlotLine
-
- columnKappa - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- columnKappa - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- columnKappa - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- columnsStatistics - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
-
- com.github.javacliparser - package com.github.javacliparser
-
- com.github.javacliparser.gui - package com.github.javacliparser.gui
-
- com.yahoo.labs.samoa.instances - package com.yahoo.labs.samoa.instances
-
- CombinationGenerator(int, int) - Constructor for class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
-
- combinationOption - Variable in class moa.classifiers.meta.DACC
-
Combination functions: MAX and WVD (MAX leads to a faster reactivity to the change, WVD is more robust to noise)
- combine(SphereCluster) - Method in class moa.cluster.SphereCluster
-
- combinePredictions(Prediction[], Instance) - Static method in class moa.classifiers.multilabel.meta.OzaBagML
-
- combSort11(double[], int[]) - Static method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
sorts the two given arrays.
- compareTo(Object) - Method in class moa.gui.experimentertab.statisticaltests.Pareja
-
- compareTo(AttributeSplitSuggestion) - Method in class moa.classifiers.core.AttributeSplitSuggestion
-
- compareTo(DACC.Pair) - Method in class moa.classifiers.meta.DACC.Pair
-
- compareTo(AttributeExpansionSuggestion) - Method in class moa.classifiers.rules.multilabel.core.AttributeExpansionSuggestion
-
- compareTo(StreamObj) - Method in class moa.clusterers.outliers.AbstractC.StreamObj
-
- compareTo(StreamObj) - Method in class moa.clusterers.outliers.Angiulli.StreamObj
-
- compareTo(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- compareTo(MCODBase.EventItem) - Method in class moa.clusterers.outliers.MCOD.MCODBase.EventItem
-
- compareTo(MicroCluster) - Method in class moa.clusterers.outliers.MCOD.MicroCluster
-
- compareTo(StreamObj) - Method in class moa.clusterers.outliers.MCOD.StreamObj
-
- compareTo(MyBaseOutlierDetector.Outlier) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.Outlier
-
- compareTo(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- compareTo(SimpleCODBase.EventItem) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventItem
-
- compareTo(StreamObj) - Method in class moa.clusterers.outliers.SimpleCOD.StreamObj
-
- compareTo(BasicAUCImbalancedPerformanceEvaluator.Estimator.Score) - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator.Score
-
Sort descending based on score value.
- compareTo(WindowAUCImbalancedPerformanceEvaluator.Estimator.Score) - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator.Score
-
Sort descending based on score value.
- compareTo(RankPerAlgorithm) - Method in class moa.gui.experimentertab.statisticaltests.RankPerAlgorithm
-
- compareTo(Pair<T, U>) - Method in class moa.recommender.rc.utils.Pair
-
- compilePredictions(Classifier[], Example) - Static method in class moa.classifiers.multilabel.meta.OzaBagML
-
- compileVotes(Classifier[], Instance) - Static method in class moa.classifiers.multilabel.meta.OzaBagML
-
- complementSet(int[], int[]) - Static method in class moa.classifiers.rules.core.Utils
-
- COMPLETED - moa.gui.experimentertab.ExpTaskThread.Status
-
- COMPLETED - moa.tasks.TaskThread.Status
-
- componentHidden(ComponentEvent) - Method in class moa.gui.outliertab.OutlierVisualTab
-
- componentHidden(ComponentEvent) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- componentHidden(ComponentEvent) - Method in class moa.gui.visualization.StreamPanel
-
- componentMoved(ComponentEvent) - Method in class moa.gui.outliertab.OutlierVisualTab
-
- componentMoved(ComponentEvent) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- componentMoved(ComponentEvent) - Method in class moa.gui.visualization.StreamPanel
-
- componentResized(ComponentEvent) - Method in class moa.gui.outliertab.OutlierVisualTab
-
- componentResized(ComponentEvent) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- componentResized(ComponentEvent) - Method in class moa.gui.visualization.StreamPanel
-
- componentShown(ComponentEvent) - Method in class moa.gui.outliertab.OutlierVisualTab
-
- componentShown(ComponentEvent) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- componentShown(ComponentEvent) - Method in class moa.gui.visualization.StreamPanel
-
- ComposedSplitFunction<DATA> - Class in moa.clusterers.outliers.utils.mtree
-
- ComposedSplitFunction(PromotionFunction<DATA>, PartitionFunction<DATA>) - Constructor for class moa.clusterers.outliers.utils.mtree.ComposedSplitFunction
-
- compress(long) - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- compressBlock(SEEDChangeDetector.SEEDBlock) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- compressBuckets() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- compressTermSEEDOption - Variable in class moa.classifiers.core.driftdetection.SEEDChangeDetector
-
- computeAnomalySupervised(RuleClassification, int, Instance) - Method in class moa.classifiers.rules.RuleClassifier
-
- computeAnomalyUnsupervised(RuleClassification, int, Instance) - Method in class moa.classifiers.rules.RuleClassifier
-
- computeBandBoundaries(long) - Static method in class moa.core.GreenwaldKhannaQuantileSummary
-
- computeBound(double, double) - Static method in class moa.classifiers.trees.iadem.IademCommonProcedures
-
- computeBranchSplitMerits(double[][]) - Method in interface moa.classifiers.rules.core.splitcriteria.AMRulesSplitCriterion
-
- computeBranchSplitMerits(double[][]) - Method in class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRules
-
- computeBranchSplitMerits(double[][]) - Method in class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRulesNode
-
- computeBranchSplitMerits(double[][]) - Method in class moa.classifiers.rules.core.splitcriteria.VarianceRatioSplitCriterion
-
- computeBranchSplitMerits(double[][]) - Method in class moa.classifiers.rules.core.splitcriteria.VRSplitCriterion
-
- computeCandidateWeight(Classifier, Instances, int) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Computes the weight of a candidate classifier.
- computeClassDist(double[][][]) - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- computeClassDist(double[][][]) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- computeClassDist(double[][][]) - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- computeClassDist(double[][][]) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- computeClassDistBinaryTest(double[][][], double[][][]) - Method in class moa.classifiers.trees.iadem.Iadem2.NominalVirtualNode
-
- computeClassDistProbabilities(double[][][], double[][][], double[][], boolean) - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- computeClassDistProbabilities(double[][][], double[][][], double[][], boolean) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- computeClassDistProbabilities(double[][][], double[][][], double[][], boolean) - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- computeClassDistProbabilities(double[][][], double[][][], double[][], boolean) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- computeConditionalProb(ArrayList<Double>, double) - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- computeConditionalProb(ArrayList<Double>, double) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- computeConditionalProb(ArrayList<Double>, double) - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- computeConditionalProb(ArrayList<Double>, double) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- computeConditionalProbability(double) - Method in class moa.classifiers.trees.iadem.Iadem2.NominalVirtualNode
-
- computeConditionalProbability(double) - Method in class moa.classifiers.trees.iadem.Iadem2.NumericVirtualNode
-
- computeConditionalProbability(double) - Method in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- computeConditionalProbPerBin(ArrayList<Double>) - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- computeConditionalProbPerBin(ArrayList<Double>) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- computeConditionalProbPerBin(ArrayList<Double>) - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- computeConditionalProbPerBin(ArrayList<Double>) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- computeEntropy(double[]) - Static method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
-
- computeEntropy(double[]) - Static method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterionMultilabel
-
- computeEntropy(double[][]) - Static method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
-
- computeEntropy(double, double) - Static method in class moa.classifiers.rules.core.Utils
-
- computeEntropy(DoubleVector) - Static method in class moa.classifiers.rules.core.Utils
-
- computeError(Instance) - Method in class moa.classifiers.rules.core.Rule
-
- computeError(Instance) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- computeError(Instance) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- computeGini(double[]) - Static method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
-
- computeGini(double[], double) - Static method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
-
- computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.trees.ARFFIMTDD
-
- computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.trees.EFDT
-
- computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.trees.FIMTDD
-
- computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.trees.HoeffdingOptionTree
-
- computeHoeffdingBound(double, double, double) - Static method in class moa.classifiers.trees.HoeffdingTree
-
- ComputeHoeffdingBound(double, double, double) - Method in class moa.classifiers.rules.RuleClassifier
-
- computeLevel(ArrayList<Double>, ArrayList<Integer>, double) - Static method in class moa.classifiers.trees.iadem.IademCommonProcedures
-
- computeMean(double, int) - Method in class moa.classifiers.rules.RuleClassifier
-
- computeMeritOfExistingSplit(SplitCriterion, double[]) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- computeMse(Classifier, Instances) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Computes the MSE of a learner for a given chunk of examples.
- computeMseR() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Computes the MSEr threshold.
- computeMseR() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Computes the MSEr threshold.
- computeMseR() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Computes the MSEr threshold.
- computePerformanceMeasure(Algorithm) - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- computeProbability(double, double, double) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- computeProbability(double, double, double) - Method in class moa.classifiers.rules.RuleClassifier
-
- computeSD(double[]) - Static method in class moa.classifiers.core.splitcriteria.SDRSplitCriterion
-
- computeSD(double[]) - Static method in class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
-
- computeSD(double, double, double) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- computeSD(double, double, double) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- computeSD(double, double, double) - Static method in class moa.classifiers.rules.core.Utils
-
- computeSD(double, double, double) - Method in class moa.classifiers.rules.functions.Perceptron
-
- computeSD(double, double, double) - Method in class moa.classifiers.trees.ARFFIMTDD
-
- computeSD(double, double, double) - Method in class moa.classifiers.trees.FIMTDD
-
- computeSD(double, double, int) - Method in class moa.classifiers.rules.RuleClassifier
-
- computeSD(double, double, long) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- computeSD(DoubleVector) - Static method in class moa.classifiers.rules.core.Utils
-
- computeValue(DoubleVector) - Method in class moa.gui.experimentertab.Measure
-
Calculates the value of measure
- computeVariance(double, double, double) - Static method in class moa.classifiers.rules.core.Utils
-
- computeVariance(DoubleVector) - Static method in class moa.classifiers.rules.core.Utils
-
- computeWeight(int, Instance) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Computes the weight of a learner before training a given example.
- computeWeight(Classifier, Instances) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Computes the weight of a given classifie.
- computeWeightedVote() - Method in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
-
- computeWeightedVote() - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote
-
Computes the weighted vote.
- computeWeightedVote() - Method in class moa.classifiers.rules.core.voting.ExpNegErrorWeightedVote
-
- computeWeightedVote() - Method in class moa.classifiers.rules.core.voting.InverseErrorWeightedVote
-
- computeWeightedVote() - Method in class moa.classifiers.rules.core.voting.MinErrorWeightedVote
-
- computeWeightedVote() - Method in class moa.classifiers.rules.core.voting.OneMinusErrorWeightedVote
-
- computeWeightedVote() - Method in class moa.classifiers.rules.core.voting.UniformWeightedVote
-
- computeWeightedVote() - Method in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- computeWeightedVote() - Method in interface moa.classifiers.rules.multilabel.core.voting.ErrorWeightedVoteMultiLabel
-
Computes the weighted vote.
- computeWeightedVote() - Method in class moa.classifiers.rules.multilabel.core.voting.FirstHitVoteMultiLabel
-
- computeWeightedVote() - Method in class moa.classifiers.rules.multilabel.core.voting.InverseErrorWeightedVoteMultiLabel
-
- computeWeightedVote() - Method in class moa.classifiers.rules.multilabel.core.voting.UniformWeightedVoteMultiLabel
-
- computeWinsTiesLossesHTML(String) - Method in class moa.gui.experimentertab.Summary
-
Generates a HTML summary that shows the gains, loses or ties of each
algorithm against each other, in a specific measure..
- computeWinsTiesLossesLatex(String) - Method in class moa.gui.experimentertab.Summary
-
Generates a latex summary that shows the gains, loses or ties of each
algorithm against each other, in a specific measure..
- CONCEPT_DRIFT - moa.gui.experimentertab.ExpPreviewPanel.TypePanel
-
- CONCEPT_DRIFT - moa.gui.PreviewPanel.TypePanel
-
- ConceptDriftGenerator - Interface in moa.streams.generators.cd
-
- ConceptDriftMainTask - Class in moa.gui.experimentertab.tasks
-
- ConceptDriftMainTask - Class in moa.tasks
-
- ConceptDriftMainTask() - Constructor for class moa.gui.experimentertab.tasks.ConceptDriftMainTask
-
- ConceptDriftMainTask() - Constructor for class moa.tasks.ConceptDriftMainTask
-
- ConceptDriftRealStream - Class in moa.streams
-
Stream generator that adds concept drift to examples in a stream with
different classes and attributes.
- ConceptDriftRealStream() - Constructor for class moa.streams.ConceptDriftRealStream
-
- ConceptDriftStream - Class in moa.streams
-
Stream generator that adds concept drift to examples in a stream.
- ConceptDriftStream() - Constructor for class moa.streams.ConceptDriftStream
-
- ConceptDriftTabPanel - Class in moa.gui
-
This panel allows the user to select and configure a task, and run it.
- ConceptDriftTabPanel() - Constructor for class moa.gui.ConceptDriftTabPanel
-
- concepts - Static variable in class moa.streams.generators.AssetNegotiationGenerator
-
- Conditional - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- confidenceChoiceOption - Variable in class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- confidenceLevelOption - Variable in class moa.classifiers.core.statisticaltests.Cramer
-
- config - Variable in class moa.options.AbstractOptionHandler
-
- Configurable - Interface in com.github.javacliparser
-
Configurable interface.
- configureTaskButton - Variable in class moa.gui.active.ALTaskManagerPanel
-
- configureTaskButton - Variable in class moa.gui.AuxiliarTaskManagerPanel
-
- configureTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- configureTaskButton - Variable in class moa.gui.featureanalysis.FeatureImportancePanel
-
- configureTaskButton - Variable in class moa.gui.MultiLabelTaskManagerPanel
-
- configureTaskButton - Variable in class moa.gui.MultiTargetTaskManagerPanel
-
- configureTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
-
- configureTaskButton - Variable in class moa.gui.TaskManagerPanel
-
- confKOption - Variable in class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- ConfStream - Class in moa.clusterers.meta
-
- ConfStream() - Constructor for class moa.clusterers.meta.ConfStream
-
- confusionMatrixBal - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- confusionMatrixLearner - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- confusionMatrixReset - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- confusionMatrixResetBal - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- connectivity - Variable in class moa.evaluation.CMM_GTAnalysis.CMMPoint
-
the connectivity of the point to its cluster
- constantLearningRatioDecayOption - Variable in class moa.classifiers.rules.AMRulesRegressorOld
-
- constantLearningRatioDecayOption - Variable in class moa.classifiers.rules.core.Rule.Builder
-
- constantLearningRatioDecayOption - Variable in class moa.classifiers.rules.functions.Perceptron
-
- constantLearningRatioDecayOption - Variable in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- contains(int, int) - Method in class moa.gui.visualization.ClusterPanel
-
- contains(int, int) - Method in class moa.gui.visualization.OutlierPanel
-
- contextIsCompatible(InstancesHeader, InstancesHeader) - Static method in class moa.classifiers.AbstractClassifier
-
Returns if two contexts or headers of instances are compatible.
Two contexts are compatible if they follow the following rules:
Rule 1: num classes can increase but never decrease
Rule 2: num attributes can increase but never decrease
Rule 3: num nominal attribute values can increase but never decrease
Rule 4: attribute types must stay in the same order (although class
can move; is always skipped over)
Attribute names are free to change, but should always still represent
the original attributes.
- contextIsCompatible(InstancesHeader, InstancesHeader) - Static method in class moa.clusterers.AbstractClusterer
-
- Converter - Class in moa.core.utils
-
Converter.
- Converter() - Constructor for class moa.core.utils.Converter
-
- Converter(int) - Constructor for class moa.core.utils.Converter
-
- convertNewLines(String) - Static method in class moa.core.Utils
-
Converts carriage returns and new lines in a string into \r and \n.
- convertToRelativePath(File) - Static method in class moa.core.Utils
-
Converts a File's absolute path to a path relative to the user
(ie start) directory.
- convertX(double) - Method in class moa.gui.LineGraphViewPanel.PlotLine
-
- convertY(double) - Method in class moa.gui.LineGraphViewPanel.PlotLine
-
- copy() - Method in class com.github.javacliparser.AbstractOption
-
- copy() - Method in interface com.github.javacliparser.Option
-
Gets a copy of this option
- copy() - Method in class com.yahoo.labs.samoa.instances.DenseInstanceData
-
- copy() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Copy.
- copy() - Method in interface com.yahoo.labs.samoa.instances.InstanceData
-
Produces a shallow copy of this instance data.
- copy() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Copy.
- copy() - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
- copy() - Method in class moa.AbstractMOAObject
-
- copy() - Method in class moa.classifiers.AbstractClassifier
-
- copy() - Method in interface moa.classifiers.Classifier
-
Produces a copy of this learner.
- copy() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Produces a copy of this change detector method
- copy() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector
-
Produces a copy of this drift detection method
- copy() - Method in class moa.classifiers.rules.core.anomalydetection.AbstractAnomalyDetector
-
- copy() - Method in interface moa.classifiers.rules.core.anomalydetection.AnomalyDetector
-
- copy() - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote
-
Creates a copy of the object
- copy() - Method in interface moa.classifiers.rules.multilabel.core.voting.ErrorWeightedVoteMultiLabel
-
Creates a copy of the object
- copy() - Method in class moa.clusterers.AbstractClusterer
-
- copy() - Method in interface moa.clusterers.Clusterer
-
- copy() - Method in class moa.clusterers.denstream.MicroCluster
-
- copy() - Method in class moa.clusterers.meta.BooleanParameter
-
- copy() - Method in class moa.clusterers.meta.CategoricalParameter
-
- copy() - Method in class moa.clusterers.meta.IntegerParameter
-
- copy() - Method in interface moa.clusterers.meta.IParameter
-
- copy() - Method in class moa.clusterers.meta.NumericalParameter
-
- copy() - Method in class moa.clusterers.meta.OrdinalParameter
-
- copy() - Method in class moa.core.AutoExpandVector
-
- copy() - Method in interface moa.core.Example
-
- copy() - Method in class moa.core.InstanceExample
-
- copy() - Method in interface moa.MOAObject
-
This method produces a copy of this object.
- copy() - Method in class moa.options.AbstractOptionHandler
-
- copy() - Method in interface moa.options.OptionHandler
-
This method produces a copy of this object.
- copy() - Method in class moa.recommender.rc.utils.DenseVector
-
- copy() - Method in class moa.recommender.rc.utils.SparseVector
-
- copy() - Method in class moa.recommender.rc.utils.Vector
-
- copy(SeqDrift2ChangeDetector.Reservoir) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Reservoir
-
- copy(SingleVector[]) - Static method in class moa.classifiers.rules.core.Utils
-
- copy(DoubleVector[]) - Static method in class moa.classifiers.rules.core.Utils
-
- copy(DoubleVector[][]) - Static method in class moa.classifiers.rules.core.Utils
-
- copy(MOAObject) - Static method in class moa.AbstractMOAObject
-
This method produces a copy of an object.
- copyAsFloatVector(DoubleVector[]) - Static method in class moa.classifiers.rules.core.Utils
-
- copyClipBoardConfiguration() - Method in class moa.gui.active.ALTaskManagerPanel
-
- copyClipBoardConfiguration() - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- copyClipBoardConfiguration() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- copyClipBoardConfiguration() - Method in class moa.gui.featureanalysis.FeatureImportancePanel
-
- copyClipBoardConfiguration() - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- copyClipBoardConfiguration() - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- copyClipBoardConfiguration() - Method in class moa.gui.RegressionTaskManagerPanel
-
- copyClipBoardConfiguration() - Method in class moa.gui.TaskManagerPanel
-
- copyInstances(int, Instances, int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
- copyObject(Serializable) - Static method in class com.github.javacliparser.SerializeUtils
-
- copyObject(Serializable) - Static method in class moa.core.SerializeUtils
-
- copyrightNotice - Static variable in class moa.core.Globals
-
- copyStatistics(ISOUPTree.Node) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- copyStatistics(ARFFIMTDD.Node) - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- copyStatistics(FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.Node
-
- copyTree(Iadem3Subtree) - Method in class moa.classifiers.trees.iadem.Iadem3
-
- CoresetCostTriple - Class in moa.clusterers.streamkm
-
CoresetCostTriple is a wrapper that allows the lloydPlusPlus method in StreamKM to return the coresetCentres,
radii of the associated clusters and the cost associated with the coreset.
- CoresetCostTriple(Point[], double[], double) - Constructor for class moa.clusterers.streamkm.CoresetCostTriple
-
- CoresetKMeans - Class in moa.clusterers.kmeanspm
-
Provides methods to execute the k-means and k-means++ algorithm with a
clustering.
- CoresetKMeans() - Constructor for class moa.clusterers.kmeanspm.CoresetKMeans
-
- coresetsize - Variable in class moa.clusterers.streamkm.StreamKM
-
- correctlyClassifies(Instance) - Method in class moa.classifiers.AbstractClassifier
-
- correctlyClassifies(Instance) - Method in interface moa.classifiers.Classifier
-
Gets whether this classifier correctly classifies an instance.
- correctlyInitialized() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Checks whether an object of this class has been correctly
initialized.
- correctPositivePredictions - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- correctPositivePredictions - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- correctPredictions - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- correctPredictions - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- CorrectWeight - Variable in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
-
- correlation(double[], double[], int) - Static method in class moa.core.Utils
-
Returns the correlation coefficient of two double vectors.
- costLabeling - Variable in class moa.classifiers.active.ALUncertainty
-
- costNegative - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- costNegative - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- costNegativeOption - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- costNegativeOption - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- costOfPoint(int, Point[]) - Method in class moa.clusterers.streamkm.Point
-
Computes the cost of this point with the given array of centres centres[] (of size k)
- costOfPointToCenter(Point) - Method in class moa.clusterers.streamkm.Point
-
Computes the cost of this point with centre centre
- costPositive - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- costPositive - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- costPositiveOption - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- costPositiveOption - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- count() - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Deprecated.
- count_after - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM.ISBNodeAppr
-
- count_after - Variable in class moa.clusterers.outliers.Angiulli.ExactSTORM.ISBNodeExact
-
- count_after - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- count_after - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- count_before - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM.ISBNodeAppr
-
- CountPrecNeighs(Long) - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM.ISBNodeExact
-
- CountPrecNeighs(Long) - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- CountPrecNeighs(Long) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- countRatingsItem(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- countRatingsItem(int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- countRatingsUser(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- countRatingsUser(int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- countTweets - Variable in class moa.streams.generators.TextGenerator
-
- coversAllOutputs() - Method in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- coversAllOutputs() - Method in interface moa.classifiers.rules.multilabel.core.voting.ErrorWeightedVoteMultiLabel
-
Check if vote has a value for each output
- Cramer - Class in moa.classifiers.core.statisticaltests
-
Implements the Multivariate Non-parametric Cramer Von Mises Statistical Test.
- Cramer() - Constructor for class moa.classifiers.core.statisticaltests.Cramer
-
- CRAMER - Static variable in class moa.classifiers.core.statisticaltests.Cramer
-
- Cramer.CramerTest - Class in moa.classifiers.core.statisticaltests
-
- cramerTest(List<Instance>, List<Instance>) - Method in class moa.classifiers.core.statisticaltests.Cramer
-
- cramerTest(List<Instance>, List<Instance>, double, int, String, boolean, int, double, int) - Method in class moa.classifiers.core.statisticaltests.Cramer
-
- CramerTest(int, int, int, double, double, double, double, double, double, double[], double[], double[]) - Constructor for class moa.classifiers.core.statisticaltests.Cramer.CramerTest
-
- cramerTest1(List<List<Double>>, List<List<Double>>) - Method in class moa.classifiers.core.statisticaltests.Cramer
-
- cramerTest1(List<List<Double>>, List<List<Double>>, double, int, String, boolean, int, double, int) - Method in class moa.classifiers.core.statisticaltests.Cramer
-
- createCustomEditor() - Method in class weka.gui.MOAClassOptionEditor
-
Creates the custom editor.
- createDebugOutputFile() - Method in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- createdOn - Variable in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- createdOn - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- createdOn - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- createLabelledOptionComponentListPanel(Option[], List<OptionEditComponent>) - Static method in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- createNewClassifier(Instance) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Processes a chunk.
- createObject(String[], Class<?>) - Static method in class com.github.javacliparser.ClassOption
-
- createObject(String, Class<?>) - Static method in class com.github.javacliparser.ClassOption
-
- createOptionsList() - Method in class moa.tasks.ipynb.OptionsString
-
Separates out options from command strings
- createPopupMenu(boolean, boolean, boolean, boolean, boolean) - Method in class moa.gui.experimentertab.ImagePanel
-
- createRelativePath(File) - Static method in class moa.core.Utils
-
Converts a File's absolute path to a path relative to the user
(ie start) directory.
- createRoot(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- createRoot(Instance) - Method in class moa.classifiers.trees.iadem.Iadem3
-
- createRule(Instance) - Method in class moa.classifiers.rules.RuleClassifier
-
- createTemplate(Instances) - Method in class moa.core.utils.Converter
-
- createVirtualNodes(IademNumericAttributeObserver, boolean, boolean, Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- createVirtualNodes(IademNumericAttributeObserver, boolean, boolean, Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNode
-
- createWekaClassifier(String[]) - Method in class moa.classifiers.meta.WEKAClassifier
-
- createWekaClassifier(String[]) - Method in class moa.classifiers.multilabel.MEKAClassifier
-
- crossingPoint - Variable in class moa.classifiers.meta.LearnNSE
-
- CROSSPLATFORM_LNF - Static variable in class moa.gui.LookAndFeel
-
the cross-platform LnF classname.
- CSMOTE - Class in moa.classifiers.meta.imbalanced
-
CSMOTE
- CSMOTE() - Constructor for class moa.classifiers.meta.imbalanced.CSMOTE
-
- csvFileOption - Variable in class moa.streams.clustering.SimpleCSVStream
-
- CuckooHashing<T> - Class in moa.clusterers.kmeanspm
-
Provides a hash table based on Cuckoo Hashing.
- CuckooHashing(int, int, int, Random) - Constructor for class moa.clusterers.kmeanspm.CuckooHashing
-
Creates a new hash table based on Cuckoo Hashing.
- CuckooHashing(int, Random) - Constructor for class moa.clusterers.kmeanspm.CuckooHashing
-
Creates a new hash table based on Cuckoo Hashing.
- cumulativeSum - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
-
- curItemID() - Method in interface moa.recommender.dataset.Dataset
-
- curItemID() - Method in class moa.recommender.dataset.impl.FlixsterDataset
-
- curItemID() - Method in class moa.recommender.dataset.impl.JesterDataset
-
- curItemID() - Method in class moa.recommender.dataset.impl.MovielensDataset
-
- curRating() - Method in interface moa.recommender.dataset.Dataset
-
- curRating() - Method in class moa.recommender.dataset.impl.FlixsterDataset
-
- curRating() - Method in class moa.recommender.dataset.impl.JesterDataset
-
- curRating() - Method in class moa.recommender.dataset.impl.MovielensDataset
-
- currentActivityDescription - Variable in class moa.tasks.StandardTaskMonitor
-
- currentActivityFractionComplete - Variable in class moa.tasks.StandardTaskMonitor
-
- currentChunk - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Current chunk of instances.
- currentChunk - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- currentChunk - Variable in class moa.classifiers.meta.RCD
-
- currentChunk2 - Variable in class moa.classifiers.meta.RCD
-
- currentLength() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
Gets the current length of the list.
- currentList - Variable in class com.github.javacliparser.ListOption
-
- currentSplitState - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- currentStatus - Variable in class moa.gui.experimentertab.ExpTaskThread
-
- currentStatus - Variable in class moa.tasks.TaskThread
-
- currentTask - Variable in class moa.gui.active.ALTaskManagerPanel
-
- currentTask - Variable in class moa.gui.AuxiliarTaskManagerPanel
-
- currentTask - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- currentTask - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- currentTask - Variable in class moa.gui.featureanalysis.FeatureImportancePanel
-
Configure GUI so that user can set parameters for feature importance algorithm and
trigger task execution to compute scores of feature importance.
- currentTask - Variable in class moa.gui.MultiLabelTaskManagerPanel
-
- currentTask - Variable in class moa.gui.MultiTargetTaskManagerPanel
-
- currentTask - Variable in class moa.gui.RegressionTaskManagerPanel
-
- currentTask - Variable in class moa.gui.TaskManagerPanel
-
- currentVal - Variable in class com.github.javacliparser.FloatOption
-
- currentVal - Variable in class com.github.javacliparser.IntOption
-
- currentVal - Variable in class com.github.javacliparser.StringOption
-
- currentValue - Variable in class com.github.javacliparser.AbstractClassOption
-
The current object
- currentValue - Variable in class moa.options.AbstractClassOption
-
The current object
- currentWindow - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Current window of instance class values.
- curUserID() - Method in interface moa.recommender.dataset.Dataset
-
- curUserID() - Method in class moa.recommender.dataset.impl.FlixsterDataset
-
- curUserID() - Method in class moa.recommender.dataset.impl.JesterDataset
-
- curUserID() - Method in class moa.recommender.dataset.impl.MovielensDataset
-
- curve - Variable in class moa.gui.LineGraphViewPanel.PlotLine
-
- CusumDM - Class in moa.classifiers.core.driftdetection
-
Drift detection method based in Cusum
- CusumDM() - Constructor for class moa.classifiers.core.driftdetection.CusumDM
-
- cut_point - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
-
- cut_point - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
-
- cut_point - Variable in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
-
- cutoffOption - Variable in class moa.clusterers.CobWeb
-
- cutPointSuggestion(int) - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- cutPointSuggestion(int) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- cutPointSuggestion(int) - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- cutPointSuggestion(int) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- DACC - Class in moa.classifiers.meta
-
Dynamic Adaptation to Concept Changes.
- DACC() - Constructor for class moa.classifiers.meta.DACC
-
- DACC.Pair - Class in moa.classifiers.meta
-
This helper class is used to sort an array of pairs of integers: val and index.
- data - Variable in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Block
-
- data - Variable in class moa.clusterers.clustree.Entry
-
The actual entry data.
- data - Variable in class moa.clusterers.outliers.utils.mtree.MTree.ResultItem
-
A nearest-neighbor.
- data - Variable in class moa.recommender.rc.predictor.impl.BaselinePredictor
-
- data - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- DataObject - Class in moa.clusterers.outliers.AnyOut.util
-
This object encapsulates a data point.
- DataObject(int, Instance) - Constructor for class moa.clusterers.outliers.AnyOut.util.DataObject
-
Standard constructor for DataObject.
- dataOption - Variable in class moa.recommender.predictor.BaselinePredictor
-
- dataOption - Variable in class moa.recommender.predictor.BRISMFPredictor
-
- DataPoint - Class in moa.gui.visualization
-
- DataPoint(Instance, Integer) - Constructor for class moa.gui.visualization.DataPoint
-
- dataset - Variable in class moa.classifiers.meta.RandomRules
-
- dataset - Variable in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- dataset - Variable in class moa.streams.clustering.SimpleCSVStream
-
- dataset - Variable in class moa.streams.filters.RBFFilter
-
- dataset - Variable in class moa.streams.filters.ReLUFilter
-
- dataset - Variable in class moa.streams.filters.SelectAttributesFilter
-
- dataset() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Dataset.
- dataset() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Dataset.
- Dataset - Interface in moa.recommender.dataset
-
- DataSet - Class in moa.clusterers.outliers.AnyOut.util
-
A set of DataObjects.
- DataSet(int) - Constructor for class moa.clusterers.outliers.AnyOut.util.DataSet
-
Creates an empty set.
- DataSet(DataObject) - Constructor for class moa.clusterers.outliers.AnyOut.util.DataSet
-
Creates a Set with only the given object.
- datasetOption - Variable in class moa.tasks.EvaluateOnlineRecommender
-
- dbInitialModelPercentage - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- DBScan - Class in moa.clusterers.macro.dbscan
-
- DBScan(Clustering, double, int) - Constructor for class moa.clusterers.macro.dbscan.DBScan
-
- DDM - Class in moa.classifiers.core.driftdetection
-
Drift detection method based in DDM method of Joao Gama SBIA 2004.
- DDM() - Constructor for class moa.classifiers.core.driftdetection.DDM
-
- DDM_INCONTROL_LEVEL - Static variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- DDM_OUTCONTROL_LEVEL - Static variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- DDM_WARNING_LEVEL - Static variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- ddmLevel - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- deactivateAllLeaves() - Method in class moa.classifiers.trees.EFDT
-
- deactivateAllLeaves() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- deactivateAllLeaves() - Method in class moa.classifiers.trees.HoeffdingTree
-
- deactivateLearningNode(EFDT.ActiveLearningNode, EFDT.SplitNode, int) - Method in class moa.classifiers.trees.EFDT
-
- deactivateLearningNode(HoeffdingOptionTree.ActiveLearningNode, HoeffdingOptionTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- deactivateLearningNode(HoeffdingTree.ActiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
-
- deactivateLearningNode(HoeffdingTree.ActiveLearningNode, HoeffdingTree.SplitNode, int) - Method in class moa.classifiers.trees.HoeffdingTree
-
- debug - Variable in class moa.evaluation.CMM
-
enable/disable debug mode
- debug(String, int) - Method in class moa.classifiers.rules.AbstractAMRules
-
Print to console
- debug(String, int) - Method in class moa.classifiers.rules.core.Rule
-
- debug(String, int) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- debug(String, int) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
Print to console
- debug(String, int) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
Print to console
- debuganomaly(Instance, double, double, double) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- debugFileOption - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- debugStream - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- decay_rate - Variable in class moa.gui.visualization.ClusterPanel
-
- decay_rate - Variable in class moa.gui.visualization.OutlierPanel
-
- decayFactorOption - Variable in class moa.clusterers.dstream.Dstream
-
- decayHorizonOption - Variable in class moa.streams.clustering.ClusteringStream
-
- decayRate - Variable in class moa.gui.visualization.PointPanel
-
- decayThreshold - Variable in class moa.gui.visualization.PointPanel
-
- decayThresholdOption - Variable in class moa.streams.clustering.ClusteringStream
-
- decisionNodeCount - Variable in class moa.classifiers.trees.EFDT
-
- decisionNodeCount - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- decisionNodeCount - Variable in class moa.classifiers.trees.HoeffdingTree
-
- DecisionStump - Class in moa.classifiers.trees
-
Decision trees of one level.
Parameters:
- DecisionStump() - Constructor for class moa.classifiers.trees.DecisionStump
-
- decrCutPoint - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- default_color - Variable in class moa.gui.visualization.ClusterPanel
-
- default_color - Variable in class moa.gui.visualization.OutlierPanel
-
- default_color - Variable in class moa.gui.visualization.PointPanel
-
- DEFAULT_MIN_NODE_CAPACITY - Static variable in class moa.clusterers.outliers.utils.mtree.MTree
-
The default minimum capacity of nodes in an M-Tree, when not specified in
the constructor call.
- DEFAULT_NUM_TABLES - Static variable in class moa.clusterers.kmeanspm.CuckooHashing
-
- DEFAULT_STASH_SIZE - Static variable in class moa.clusterers.kmeanspm.CuckooHashing
-
- defaultCLIString - Variable in class com.github.javacliparser.AbstractClassOption
-
The default command line interface text.
- defaultCLIString - Variable in class moa.options.AbstractClassOption
-
The default command line interface text.
- defaultFileExtension - Variable in class com.github.javacliparser.FileOption
-
- defaultList - Variable in class com.github.javacliparser.ListOption
-
- defaultNumericAttribute - Variable in class com.yahoo.labs.samoa.instances.AttributesInformation
-
The attribute used for default for numerical values
- defaultOptionIndex - Variable in class com.github.javacliparser.MultiChoiceOption
-
- defaultRule - Variable in class moa.classifiers.rules.AbstractAMRules
-
- defaultRule - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- defaultRule - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- defaultRuleErrors(Prediction) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- defaultRuleErrors(Prediction) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- defaultVal - Variable in class com.github.javacliparser.FloatOption
-
- defaultVal - Variable in class com.github.javacliparser.IntOption
-
- defaultVal - Variable in class com.github.javacliparser.StringOption
-
- defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Initializes the format for the dataset produced.
- defineImmutableCapabilities() - Method in interface moa.capabilities.CapabilitiesHandler
-
Defines the set of capabilities the object has.
- defineImmutableCapabilities() - Method in class moa.classifiers.AbstractClassifier
-
- defineImmutableCapabilities() - Method in class moa.classifiers.bayes.NaiveBayes
-
- defineImmutableCapabilities() - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
-
- defineImmutableCapabilities() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- defineImmutableCapabilities() - Method in class moa.classifiers.functions.MajorityClass
-
- defineImmutableCapabilities() - Method in class moa.classifiers.functions.NoChange
-
- defineImmutableCapabilities() - Method in class moa.classifiers.lazy.SAMkNN
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.AdaptiveRandomForest
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.LeveragingBag
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.OzaBag
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.OzaBagAdwin
-
- defineImmutableCapabilities() - Method in class moa.classifiers.meta.StreamingRandomPatches
-
- defineImmutableCapabilities() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
-
- defineImmutableCapabilities() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- defineImmutableCapabilities() - Method in class moa.classifiers.trees.HoeffdingTree
-
- defineImmutableCapabilities() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- defineImmutableCapabilities() - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
-
- defineImmutableCapabilities() - Method in interface moa.evaluation.LearningPerformanceEvaluator
-
- defineImmutableCapabilities() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
-
- defineImmutableCapabilities() - Method in class moa.streams.ArffFileStream
-
- defineImmutableCapabilities() - Method in class moa.streams.ConceptDriftRealStream
-
- defineImmutableCapabilities() - Method in class moa.streams.ConceptDriftStream
-
- defineImmutableCapabilities() - Method in interface moa.streams.ExampleStream
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.AgrawalGenerator
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.HyperplaneGenerator
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.LEDGenerator
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.LEDGeneratorDrift
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.RandomRBFGenerator
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.RandomRBFGeneratorDrift
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.RandomTreeGenerator
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.SEAGenerator
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.STAGGERGenerator
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.WaveformGenerator
-
- defineImmutableCapabilities() - Method in class moa.streams.generators.WaveformGeneratorDrift
-
- defineImmutableCapabilities() - Method in class moa.tasks.ClassificationMainTask
-
- defineImmutableCapabilities() - Method in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- defineImmutableCapabilities() - Method in class moa.tasks.EvaluateModel
-
- defineImmutableCapabilities() - Method in class moa.tasks.EvaluatePeriodicHeldOutTest
-
- defineImmutableCapabilities() - Method in class moa.tasks.EvaluatePrequential
-
- defineImmutableCapabilities() - Method in class moa.tasks.LearnModel
-
- delay - Variable in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Delay in detecting change
- delay - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- delayLengthOption - Variable in class moa.tasks.EvaluatePrequentialDelayed
-
- delayLengthOption - Variable in class moa.tasks.EvaluatePrequentialDelayedCV
-
- delete() - Method in class com.yahoo.labs.samoa.instances.Instances
-
Delete.
- delete(int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Delete.
- deleteAttributeAt(int) - Method in class com.yahoo.labs.samoa.instances.AttributesInformation
-
- deleteAttributeAt(int) - Method in class com.yahoo.labs.samoa.instances.DenseInstanceData
-
- deleteAttributeAt(int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Delete attribute at.
- deleteAttributeAt(int) - Method in interface com.yahoo.labs.samoa.instances.InstanceData
-
Deletes an attribute.
- deleteAttributeAt(int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Delete attribute at.
- deleteAttributeAt(int) - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- deleteAttributeAt(int) - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Deletes an attribute at the given position (0 to numAttributes() - 1).
- deleteAttributeAt(Integer) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Delete attribute at.
- deleteDrectory(File) - Static method in class moa.gui.experimentertab.ReadFile
-
Delete the selected directory.
- deletedTrees - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- deleteElement() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- deleteMergeableTupleMostFull() - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- deleteNode(HoeffdingTree.Node, int) - Method in class moa.classifiers.trees.ASHoeffdingTree
-
- deleteScriptsOption - Variable in class moa.tasks.Plot
-
Determines whether to delete gnuplot scripts after plotting.
- deleteSelectedTasks() - Method in class moa.gui.active.ALTaskManagerPanel
-
- deleteSelectedTasks() - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- deleteSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- deleteSelectedTasks() - Method in class moa.gui.experimentertab.TaskManagerTabPanel
-
Deletes selected tasks
- deleteSelectedTasks() - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- deleteSelectedTasks() - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- deleteSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
-
- deleteSelectedTasks() - Method in class moa.gui.TaskManagerPanel
-
- deleteTaskButton - Variable in class moa.gui.active.ALTaskManagerPanel
-
- deleteTaskButton - Variable in class moa.gui.AuxiliarTaskManagerPanel
-
- deleteTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- deleteTaskButton - Variable in class moa.gui.MultiLabelTaskManagerPanel
-
- deleteTaskButton - Variable in class moa.gui.MultiTargetTaskManagerPanel
-
- deleteTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
-
- deleteTaskButton - Variable in class moa.gui.TaskManagerPanel
-
- deleteTuple(int) - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- deleteTupleMostFull() - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- deliveryDelayValues - Static variable in class moa.streams.generators.AssetNegotiationGenerator
-
- delta - Variable in class moa.core.GreenwaldKhannaQuantileSummary.Tuple
-
- DELTA - Static variable in class moa.classifiers.core.driftdetection.ADWIN
-
- deltaAdwinOption - Variable in class moa.classifiers.core.driftdetection.ADWINChangeDetector
-
- deltaAdwinOption - Variable in class moa.classifiers.meta.LeveragingBag
-
- deltaAdwinOption - Variable in class moa.classifiers.meta.LimAttClassifier
-
- deltaAdwinOption - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- deltaOption - Variable in class moa.classifiers.core.driftdetection.CusumDM
-
- deltaOption - Variable in class moa.classifiers.core.driftdetection.PageHinkleyDM
-
- deltaOption - Variable in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
-
- deltaSEEDOption - Variable in class moa.classifiers.core.driftdetection.SEEDChangeDetector
-
- deltaSeqDrift2Option - Variable in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
-
- deltaWarningOption - Variable in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
-
- DenseInstance - Class in com.yahoo.labs.samoa.instances
-
The Class DenseInstance.
- DenseInstance(double) - Constructor for class com.yahoo.labs.samoa.instances.DenseInstance
-
Instantiates a new dense instance.
- DenseInstance(double, double[]) - Constructor for class com.yahoo.labs.samoa.instances.DenseInstance
-
Instantiates a new dense instance.
- DenseInstance(Instance) - Constructor for class com.yahoo.labs.samoa.instances.DenseInstance
-
Instantiates a new dense instance.
- DenseInstance(InstanceImpl) - Constructor for class com.yahoo.labs.samoa.instances.DenseInstance
-
Instantiates a new dense instance.
- DenseInstanceData - Class in com.yahoo.labs.samoa.instances
-
The Class DenseInstanceData.
- DenseInstanceData() - Constructor for class com.yahoo.labs.samoa.instances.DenseInstanceData
-
Instantiates a new dense instance data.
- DenseInstanceData(double[]) - Constructor for class com.yahoo.labs.samoa.instances.DenseInstanceData
-
Instantiates a new dense instance data.
- DenseInstanceData(int) - Constructor for class com.yahoo.labs.samoa.instances.DenseInstanceData
-
Instantiates a new dense instance data.
- DenseMicroCluster - Class in moa.clusterers.macro.dbscan
-
- DenseMicroCluster(CFCluster) - Constructor for class moa.clusterers.macro.dbscan.DenseMicroCluster
-
- DenseVector - Class in moa.recommender.rc.utils
-
- DenseVector() - Constructor for class moa.recommender.rc.utils.DenseVector
-
- DenseVector(ArrayList<Double>) - Constructor for class moa.recommender.rc.utils.DenseVector
-
- DenseVector.DenseVectorIterator - Class in moa.recommender.rc.utils
-
- DenseVectorIterator() - Constructor for class moa.recommender.rc.utils.DenseVector.DenseVectorIterator
-
- DensityGrid - Class in moa.clusterers.dstream
-
Density Grids are defined in equation 3 (section 3.1) of Chen and Tu 2007 as:
In D-Stream, we partition the d−dimensional space S into density grids.
- DensityGrid(int[]) - Constructor for class moa.clusterers.dstream.DensityGrid
-
A constructor method for a density grid
- DensityGrid(DensityGrid) - Constructor for class moa.clusterers.dstream.DensityGrid
-
A constructor method for a density grid
- densityRangeOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- densityWithNew(int, double) - Method in class moa.clusterers.dstream.CharacteristicVector
-
Implements the density update function given in
eq 5 (Proposition 3.1) of Chen and Tu 2007.
- DependentOptionsUpdater - Class in moa.options
-
This class handles the dependency between two options by updating the
dependent option whenever the option it is depending on changes.
- DependentOptionsUpdater(ClassOptionWithListenerOption, EditableMultiChoiceOption) - Constructor for class moa.options.DependentOptionsUpdater
-
- descendOneStep(Instance) - Method in class moa.classifiers.trees.ARFFIMTDD.SplitNode
-
- descendOneStep(Instance) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
-
- describe() - Method in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
Describe the feature importance method used.
- describeConditionForBranch(int, InstancesHeader) - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalTest
-
Gets the text that describes the condition of a branch.
- describeConditionForBranch(int, InstancesHeader) - Method in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
-
- describeConditionForBranch(int, InstancesHeader) - Method in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
-
- describeConditionForBranch(int, InstancesHeader) - Method in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
-
- describeConditionForBranch(int, InstancesHeader) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- describeSubtree(StringBuilder, int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.LeafNode
-
- describeSubtree(StringBuilder, int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- describeSubtree(StringBuilder, int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.SplitNode
-
- describeSubtree(StringBuilder, int) - Method in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- describeSubtree(StringBuilder, int) - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- describeSubtree(StringBuilder, int) - Method in class moa.classifiers.trees.ARFFIMTDD.SplitNode
-
- describeSubtree(StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
-
- describeSubtree(StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD.Node
-
- describeSubtree(StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
-
- describeSubtree(EFDT, StringBuilder, int) - Method in class moa.classifiers.trees.EFDT.Node
-
- describeSubtree(EFDT, StringBuilder, int) - Method in class moa.classifiers.trees.EFDT.SplitNode
-
- describeSubtree(HoeffdingOptionTree, StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
-
- describeSubtree(HoeffdingOptionTree, StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- describeSubtree(HoeffdingTree, StringBuilder, int) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
-
- describeSubtree(HoeffdingTree, StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingTree.Node
-
- describeSubtree(HoeffdingTree, StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- detectMeanIncrement(HDDM_W_Test.SampleInfo, HDDM_W_Test.SampleInfo, double) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- detector - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- detectorStream - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- determineAssignments(KDTreeNode, Instances, int[], int[], double) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Assigns instances to the current centers called candidates.
- determineClass(double, double) - Method in interface moa.streams.generators.SineGenerator.ClassFunction
-
- determineClass(double, double, double) - Method in interface moa.streams.generators.SEAGenerator.ClassFunction
-
- determineClass(double, double, double, double) - Method in interface moa.streams.generators.MixedGenerator.ClassFunction
-
- determineClass(double, double, int, int, int, int, double, int, double) - Method in interface moa.streams.generators.AgrawalGenerator.ClassFunction
-
- determineClass(int, int, int) - Method in interface moa.streams.generators.STAGGERGenerator.ClassFunction
-
- determineClass(String, String, String, String, String) - Method in interface moa.streams.generators.AssetNegotiationGenerator.ClassFunction
-
- determineClusterCentreKMeans(int, Point[]) - Method in class moa.clusterers.streamkm.Point
-
Computes the index of the centre nearest to this point with the given array of centres centres[] (of size k)
- determineNumberOfClusters() - Method in class moa.clusterers.CobWeb
-
determines the number of clusters if necessary
- DietzfelbingerHash - Class in moa.clusterers.kmeanspm
-
Provides a Dietzfelbinger hash function.
- DietzfelbingerHash(int, Random) - Constructor for class moa.clusterers.kmeanspm.DietzfelbingerHash
-
Creates a Dietzfelbinger hash function.
- difference(int, double, double) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Computes the difference between two given attribute
values.
- dimension - Variable in class moa.clusterers.streamkm.StreamKM
-
- dimension() - Method in class moa.cluster.Clustering
-
- dimensions() - Method in class moa.clusterers.outliers.AbstractC.StreamObj
-
- dimensions() - Method in class moa.clusterers.outliers.Angiulli.StreamObj
-
- dimensions() - Method in class moa.clusterers.outliers.MCOD.MicroCluster
-
- dimensions() - Method in class moa.clusterers.outliers.MCOD.StreamObj
-
- dimensions() - Method in class moa.clusterers.outliers.SimpleCOD.StreamObj
-
- dimensions() - Method in interface moa.clusterers.outliers.utils.mtree.DistanceFunctions.EuclideanCoordinate
-
The number of dimensions.
- direction - Variable in class moa.gui.visualization.ClusterPanel
-
- directionForBestTree() - Method in class moa.classifiers.trees.ORTO.OptionNode
-
- disableAttribute(int) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
-
- disableAttribute(int) - Method in class moa.classifiers.trees.ARFHoeffdingTree.LearningNodeNB
-
- disableAttribute(int) - Method in class moa.classifiers.trees.EFDT.ActiveLearningNode
-
- disableAttribute(int) - Method in class moa.classifiers.trees.EFDT.LearningNodeNB
-
- disableAttribute(int) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTreeClassifLeaves.LearningNodeHATClassifier
-
- disableAttribute(int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
-
- disableAttribute(int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNB
-
- disableAttribute(int) - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
-
- disableAttribute(int) - Method in class moa.classifiers.trees.HoeffdingTree.LearningNodeNB
-
- disableAttribute(int) - Method in class moa.classifiers.trees.HoeffdingTreeClassifLeaves.LearningNodeClassifier
-
- disableAttribute(int) - Method in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNB
-
- disableAttribute(int) - Method in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNB
-
- disableBackgroundLearnerOption - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- disableBackgroundLearnerOption - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- disableBackgroundLearnerOption - Variable in class moa.classifiers.meta.StreamingRandomPatches
-
- disableBkgLearner - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- disableChangeDetection() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- disableChangeDetection() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- disableChangeDetection() - Method in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- disableChangeDetection() - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- disableChangeDetection() - Method in class moa.classifiers.trees.FIMTDD.InnerNode
-
- disableChangeDetection() - Method in class moa.classifiers.trees.FIMTDD.Node
-
- disableDriftDetectionOption - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- disableDriftDetectionOption - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- disableDriftDetectionOption - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- disableDriftDetectionOption - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- disableDriftDetectionOption - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- disableDriftDetectionOption - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- disableDriftDetectionOption - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- disableDriftDetectionOption - Variable in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- disableDriftDetectionOption - Variable in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- disableDriftDetectionOption - Variable in class moa.classifiers.meta.StreamingRandomPatches
-
- disableDriftDetector - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- disableRefresh() - Method in class moa.gui.experimentertab.ExpPreviewPanel
-
- disableRefresh() - Method in class moa.gui.PreviewPanel
-
- disableUpdates - Variable in class moa.recommender.rc.data.AbstractRecommenderData
-
- disableUpdates(boolean) - Method in class moa.recommender.rc.data.AbstractRecommenderData
-
- disableUpdates(boolean) - Method in interface moa.recommender.rc.data.RecommenderData
-
- disableWeightedVote - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- disableWeightedVote - Variable in class moa.classifiers.meta.StreamingRandomPatches
-
- discardModel(int) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Removes the classifier at a given index from the model, thus decreasing
the models size.
- discardModel(int) - Method in class moa.classifiers.meta.DACC
-
Resets a classifier in the ensemble
- discardModel(int) - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- discardNexInstancesNotFromPartition() - Method in class moa.streams.PartitioningStream
-
discarding all instances which are exluded until an instance which can be seen by this
stream or the stream is empty
- discoverOptionsViaReflection() - Method in class com.github.javacliparser.JavaCLIParser
-
Gets the options of this class via reflection.
- DiscreteAttributeClassObserver - Interface in moa.classifiers.core.attributeclassobservers
-
Interface for observing the class data distribution for a discrete (nominal) attribute.
- distance - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeapElement
-
the distance of this element.
- distance - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBSearchResult
-
- distance - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBSearchResult
-
- distance - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBSearchResult
-
- distance - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBSearchResult
-
- distance - Variable in class moa.clusterers.outliers.utils.mtree.MTree.ResultItem
-
The distance from the nearest-neighbor to the query data object
parameter.
- distance(double[]) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the Euclidean length of a point.
- distance(double[], double[]) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the Euclidean distance of two points.
- distance(double[], double[], int) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the Euclidean distance of two points.
- distance(Instance, Instance) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction
-
Calculates the distance between two instances.
- distance(Instance, Instance) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance
-
Calculates the distance between two instances.
- distance(Instance, Instance) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Calculates the distance between two instances.
- distance(Instance, Instance, double) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction
-
Calculates the distance between two instances.
- distance(Instance, Instance, double) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Calculates the distance between two instances.
- distanceFunction - Variable in class moa.clusterers.outliers.utils.mtree.MTree
-
- DistanceFunction - Interface in moa.classifiers.lazy.neighboursearch
-
Interface for any class that can compute and return distances between two
instances.
- DistanceFunction<DATA> - Interface in moa.clusterers.outliers.utils.mtree
-
An object that can calculate the distance between two data objects.
- DistanceFunctions - Class in moa.clusterers.outliers.utils.mtree
-
- DistanceFunctions.EuclideanCoordinate - Interface in moa.clusterers.outliers.utils.mtree
-
An interface to represent coordinates in Euclidean spaces.
- distanceFunctionTipText() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Returns the tip text for this property.
- distanceSquared(double[]) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the squared Euclidean length of a point.
- distanceSquared(double[], double[]) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the squared Euclidean distance of two points.
- distanceSquared(double[], double[], int) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the squared Euclidean distance of two points.
- distanceToHrect(KDTreeNode, Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns the distance between a point and an hyperrectangle.
- distanceWithDivision(double[], double) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the Euclidean length of a point divided by a scalar.
- distanceWithDivision(double[], double, double[]) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the Euclidean distance of the first point divided by a scalar and
another second point.
- distanceWithDivision(double[], double, double[], double) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the Euclidean distance of the first point divided by a first scalar
and another second point divided by a second scalar.
- distanceWithDivisionSquared(double[], double) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the squared Euclidean length of a point divided by a scalar.
- distanceWithDivisionSquared(double[], double, double[]) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the squared Euclidean distance of the first point divided by a
scalar and another second point.
- distanceWithDivisionSquared(double[], double, double[], double) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the squared Euclidean distance of the first point divided by a
first scalar and another second point divided by a second scalar.
- distributionForInstance(Instance) - Method in class weka.classifiers.meta.MOA
-
Predicts the class memberships for a given instance.
- dloss(double) - Method in class moa.classifiers.functions.SGD
-
- dloss(double) - Method in class moa.classifiers.functions.SGDMultiClass
-
- dloss(double) - Method in class moa.classifiers.functions.SPegasos
-
- doLabelAcqReport(Example<Instance>, int) - Method in interface moa.evaluation.ALClassificationPerformanceEvaluator
-
Reports if a label of an instance was acquired.
- doLabelAcqReport(Example<Instance>, int) - Method in class moa.evaluation.ALWindowClassificationPerformanceEvaluator
-
Receives the information if a label has been acquired and increases counters.
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateClustering
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateConceptDrift
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateInterleavedChunks
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateModel
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateModelMultiLabel
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateModelMultiTarget
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateModelRegression
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateMultipleClusterings
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluateOnlineRecommender
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePeriodicHeldOutTest
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePrequential
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePrequentialCV
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePrequentialDelayed
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePrequentialDelayedCV
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePrequentialMultiLabel
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePrequentialMultiTarget
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.EvaluatePrequentialRegression
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.FeatureImportanceConfig
-
After user clicks Run button, this method executes task to compute scores of feature importance and return.
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.LearnModel
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.LearnModelMultiLabel
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.LearnModelMultiTarget
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.LearnModelRegression
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.MainTask
-
This method performs this task.
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.MeasureStreamSpeed
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.meta.ALMultiParamTask
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.meta.ALPartitionEvaluationTask
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.meta.ALPrequentialEvaluationTask
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.Plot
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.RunStreamTasks
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.RunTasks
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.WriteConfigurationToJupyterNotebook
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.WriteMultipleStreamsToARFF
-
- doMainTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.WriteStreamToARFFFile
-
- doMeasure(ArrayList<Double>) - Method in class moa.classifiers.trees.iadem.IademSplitCriterion
-
- DominantLabelsClassifier - Class in moa.classifiers.rules.multilabel.functions
-
- DominantLabelsClassifier() - Constructor for class moa.classifiers.rules.multilabel.functions.DominantLabelsClassifier
-
- doNaiveBayesPrediction(Instance, DoubleVector, AutoExpandVector<AttributeClassObserver>) - Static method in class moa.classifiers.bayes.NaiveBayes
-
- doNaiveBayesPredictionLog(Instance, DoubleVector, AutoExpandVector<AttributeClassObserver>, AutoExpandVector<AttributeClassObserver>) - Static method in class moa.classifiers.bayes.NaiveBayes
-
- doNotNormalizeFeatureScore() - Method in class moa.tasks.FeatureImportanceConfig
-
- doNotNormalizeFeatureScoreOption - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- doNotNormalizeOption - Variable in class moa.classifiers.multilabel.trees.ISOUPTree
-
- doNotOutputResultsToFileOption - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- dontNormalizeTipText() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Returns the tip text for this property.
- doSaveAs() - Method in class moa.gui.experimentertab.ImagePanel
-
Method for save the images.
- doSplit(IademAttributeSplitSuggestion, Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- doSplit(IademAttributeSplitSuggestion, Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNode
-
- doTask() - Method in class moa.tasks.AbstractTask
-
- doTask() - Method in interface moa.tasks.Task
-
This method performs this task,
when TaskMonitor and ObjectRepository are no needed.
- doTask(TaskMonitor, ObjectRepository) - Method in class moa.tasks.AbstractTask
-
- doTask(TaskMonitor, ObjectRepository) - Method in interface moa.tasks.Task
-
This method performs this task.
- DoTask - Class in moa
-
Class for running a MOA task from the command line.
- DoTask() - Constructor for class moa.DoTask
-
- doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.gui.experimentertab.tasks.EvaluateConceptDrift
-
- doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.gui.experimentertab.tasks.EvaluateInterleavedChunks
-
- doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.gui.experimentertab.tasks.EvaluateInterleavedTestThenTrain
-
- doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.gui.experimentertab.tasks.EvaluatePeriodicHeldOutTest
-
- doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.gui.experimentertab.tasks.EvaluatePrequential
-
- doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.gui.experimentertab.tasks.EvaluatePrequentialCV
-
- doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.tasks.AbstractTask
-
This method performs this task.
- doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.tasks.CacheShuffledStream
-
- doTaskImpl(TaskMonitor, ObjectRepository) - Method in class moa.tasks.MainTask
-
- dotProd(Instance, double[], int) - Static method in class moa.classifiers.functions.SPegasos
-
- dotProd(Instance, DoubleVector, int) - Static method in class moa.classifiers.functions.SGD
-
- dotProd(Instance, DoubleVector, int) - Static method in class moa.classifiers.functions.SGDMultiClass
-
- dotProduct(double[]) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the dot product of the point with itself.
- dotProduct(double[], double[]) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the dot product of the first point with a second point.
- dotProduct(Vector) - Method in class moa.recommender.rc.utils.Vector
-
- dotProductWithAddition(double[], double[], double[]) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the dot product of the addition of the first and the second
point with the third point.
- dotProductWithAddition(double[], double[], double[], double[]) - Static method in class moa.clusterers.kmeanspm.Metric
-
Calculates the dot product of the addition of the first and the second
point with the addition of the third and the fourth point.
- DOTS - moa.gui.experimentertab.PlotTab.PlotStyle
-
- DOTS - moa.tasks.Plot.PlotStyle
-
- DOUBLE_ADD - Static variable in class moa.clusterers.clustree.util.SimpleBudget
-
- DOUBLE_DIV - Static variable in class moa.clusterers.clustree.util.SimpleBudget
-
- DOUBLE_MULT - Static variable in class moa.clusterers.clustree.util.SimpleBudget
-
- doubleAddition() - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget class that a double addition has been
performed by the tree.
- doubleAddition() - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- doubleAddition(int) - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget that a certain number of double additions
have been performed.
- doubleAddition(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- doubleDivision() - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget class that a double division has
been performed by the tree.
- doubleDivision() - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- doubleDivision(int) - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget that a certain number of double divisions
have been performed.
- doubleDivision(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- doubleMultiplication() - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget class that a double multiplicaton has
been performed by the tree.
- doubleMultiplication() - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- doubleMultiplication(int) - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget that a certain number of double
multiplications have been performed.
- doubleMultiplication(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- doubleToCLIString(double) - Static method in class com.github.javacliparser.FloatOption
-
- doubleToString(double, int) - Static method in class com.github.javacliparser.StringUtils
-
- doubleToString(double, int) - Static method in class moa.core.StringUtils
-
- doubleToString(double, int) - Static method in class moa.core.Utils
-
Rounds a double and converts it into String.
- doubleToString(double, int, int) - Static method in class com.github.javacliparser.StringUtils
-
- doubleToString(double, int, int) - Static method in class moa.core.StringUtils
-
- doubleToString(double, int, int) - Static method in class moa.core.Utils
-
Rounds a double and converts it into a formatted decimal-justified String.
- DoubleVector - Class in moa.core
-
Vector of double numbers with some utilities.
- DoubleVector() - Constructor for class moa.core.DoubleVector
-
- DoubleVector(double[]) - Constructor for class moa.core.DoubleVector
-
- DoubleVector(DoubleVector) - Constructor for class moa.core.DoubleVector
-
- downheap() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap
-
performs downheap operation for the heap
to maintian its properties.
- drawClusterings(List<DataPoint>, List<DataPoint>) - Method in class moa.gui.visualization.RunVisualizer
-
- drawEvent(OutlierEvent, boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- drawGTClustering(Clustering, List<DataPoint>, Color) - Method in class moa.gui.visualization.StreamPanel
-
- drawMacroClustering(Clustering, List<DataPoint>, Color) - Method in class moa.gui.visualization.StreamPanel
-
- drawMicroClustering(Clustering, List<DataPoint>, Color) - Method in class moa.gui.visualization.StreamPanel
-
- drawOnCanvas(Graphics2D) - Method in class moa.gui.visualization.ClusterPanel
-
- drawOnCanvas(Graphics2D) - Method in class moa.gui.visualization.OutlierPanel
-
- drawOnCanvas(Graphics2D) - Method in class moa.gui.visualization.PointPanel
-
- drawOutliers(Vector<MyBaseOutlierDetector.Outlier>, Color) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- drawPoint(DataPoint) - Method in class moa.gui.visualization.StreamPanel
-
- drawPoint(DataPoint, boolean, boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- drawXLabels(Graphics) - Method in class moa.gui.visualization.AbstractGraphAxes
-
Draws the x labels onto the x axis.
- drawXLabels(Graphics) - Method in class moa.gui.visualization.ParamGraphAxes
-
- drawXLabels(Graphics) - Method in class moa.gui.visualization.ProcessGraphAxes
-
- DRIFT - Static variable in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector.SeqDrift1
-
- driftConfidence - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- driftConfidenceOption - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- driftConfidenceOption - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- driftDetection - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- driftDetection - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- driftDetection - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- driftDetection - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- driftDetection - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- driftDetection - Variable in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- driftDetection - Variable in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- driftDetectionMethod - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- driftDetectionMethod - Variable in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- driftDetectionMethod - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- driftDetectionMethod - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- driftDetectionMethod - Variable in class moa.learners.ChangeDetectorLearner
-
- DriftDetectionMethodClassifier - Class in moa.classifiers.drift
-
Class for handling concept drift datasets with a wrapper on a
classifier.
- DriftDetectionMethodClassifier() - Constructor for class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- driftDetectionMethodOption - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- driftDetectionMethodOption - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- driftDetectionMethodOption - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- driftDetectionMethodOption - Variable in class moa.classifiers.meta.StreamingRandomPatches
-
- driftDetectionMethodOption - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- driftDetectionMethodOption - Variable in class moa.learners.ChangeDetectorLearner
-
- DriftDetectionOption - Variable in class moa.classifiers.rules.AbstractAMRules
-
- driftInstance - Variable in class moa.streams.ConceptDriftRealStream
-
- driftLevelOption - Variable in class moa.classifiers.core.driftdetection.RDDM
-
- driftOption - Variable in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- driftOption - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- driftOption - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- driftStream - Variable in class moa.streams.ConceptDriftRealStream
-
- driftStream - Variable in class moa.streams.ConceptDriftStream
-
- driftstreamOption - Variable in class moa.streams.ConceptDriftRealStream
-
- driftstreamOption - Variable in class moa.streams.ConceptDriftStream
-
- dropOldRuleAfterExpansionOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- dropOldRuleAfterExpansionOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- Dstream - Class in moa.clusterers.dstream
-
Citation: Y.
- Dstream() - Constructor for class moa.clusterers.dstream.Dstream
-
- dumpFileOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- dumpFileOption - Variable in class moa.tasks.EvaluateClustering
-
- dumpFileOption - Variable in class moa.tasks.EvaluateConceptDrift
-
- dumpFileOption - Variable in class moa.tasks.EvaluateInterleavedChunks
-
Allows to define the output file name and location.
- dumpFileOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- dumpFileOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- dumpFileOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
-
- dumpFileOption - Variable in class moa.tasks.EvaluatePrequential
-
- dumpFileOption - Variable in class moa.tasks.EvaluatePrequentialCV
-
- dumpFileOption - Variable in class moa.tasks.EvaluatePrequentialDelayed
-
- dumpFileOption - Variable in class moa.tasks.EvaluatePrequentialDelayedCV
-
- dumpFileOption - Variable in class moa.tasks.EvaluatePrequentialMultiLabel
-
- dumpFileOption - Variable in class moa.tasks.EvaluatePrequentialMultiTarget
-
- dumpFileOption - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- dumpFileOption - Variable in class moa.tasks.EvaluatePrequentialRegression
-
- dumpFileOption - Variable in class moa.tasks.meta.ALPrequentialEvaluationTask
-
- DynamicWeightedMajority - Class in moa.classifiers.meta
-
Dynamic weighted majority algorithm.
- DynamicWeightedMajority() - Constructor for class moa.classifiers.meta.DynamicWeightedMajority
-
- EDDM - Class in moa.classifiers.core.driftdetection
-
Drift detection method based in EDDM method of Manuel Baena et al.
- EDDM() - Constructor for class moa.classifiers.core.driftdetection.EDDM
-
- EditableMultiChoiceOption - Class in moa.options
-
MultiChoiceOption that can have changing options.
- EditableMultiChoiceOption(String, char, String, String[], String[], int) - Constructor for class moa.options.EditableMultiChoiceOption
-
- EditableMultiChoiceOptionEditComponent - Class in moa.gui
-
- EditableMultiChoiceOptionEditComponent(Option) - Constructor for class moa.gui.EditableMultiChoiceOptionEditComponent
-
- editButton - Variable in class com.github.javacliparser.gui.ClassOptionEditComponent
-
- editButton - Variable in class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
- editButton - Variable in class moa.gui.WEKAClassOptionEditComponent
-
- editComponent - Variable in class moa.options.EditableMultiChoiceOption
-
The corresponding UI component
- editComponents - Variable in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- editComponents - Variable in class moa.gui.clustertab.ClusteringAlgoPanel
-
- editComponents - Variable in class moa.gui.outliertab.OutlierAlgoPanel
-
- editedOption - Variable in class com.github.javacliparser.gui.ClassOptionEditComponent
-
- editedOption - Variable in class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
- editedOption - Variable in class com.github.javacliparser.gui.FileOptionEditComponent
-
- editedOption - Variable in class com.github.javacliparser.gui.FlagOptionEditComponent
-
- editedOption - Variable in class com.github.javacliparser.gui.FloatOptionEditComponent
-
- editedOption - Variable in class com.github.javacliparser.gui.IntOptionEditComponent
-
- editedOption - Variable in class com.github.javacliparser.gui.MultiChoiceOptionEditComponent
-
- editedOption - Variable in class com.github.javacliparser.gui.StringOptionEditComponent
-
- editedOption - Variable in class moa.gui.WEKAClassOptionEditComponent
-
- editObject() - Method in class com.github.javacliparser.gui.ClassOptionEditComponent
-
- editObject() - Method in class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
- editObject() - Method in class moa.gui.WEKAClassOptionEditComponent
-
- EFDT - Class in moa.classifiers.trees
-
- EFDT() - Constructor for class moa.classifiers.trees.EFDT
-
- EFDT.ActiveLearningNode - Class in moa.classifiers.trees
-
- EFDT.EFDTLearningNode - Class in moa.classifiers.trees
-
- EFDT.EFDTNode - Interface in moa.classifiers.trees
-
- EFDT.EFDTSplitNode - Class in moa.classifiers.trees
-
- EFDT.FoundNode - Class in moa.classifiers.trees
-
- EFDT.InactiveLearningNode - Class in moa.classifiers.trees
-
- EFDT.LearningNode - Class in moa.classifiers.trees
-
- EFDT.LearningNodeNB - Class in moa.classifiers.trees
-
- EFDT.LearningNodeNBAdaptive - Class in moa.classifiers.trees
-
- EFDT.Node - Class in moa.classifiers.trees
-
- EFDT.SplitNode - Class in moa.classifiers.trees
-
- EFDTLearningNode(double[]) - Constructor for class moa.classifiers.trees.EFDT.EFDTLearningNode
-
- EFDTSplitNode(InstanceConditionalTest, double[]) - Constructor for class moa.classifiers.trees.EFDT.EFDTSplitNode
-
- EFDTSplitNode(InstanceConditionalTest, double[], int) - Constructor for class moa.classifiers.trees.EFDT.EFDTSplitNode
-
- effectiveNearestNeighbors - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- elementAt(int) - Method in class moa.core.FastVector
-
Returns the element at the given position.
- EMProjectedClustering - Class in moa.clusterers.outliers.AnyOut.util
-
Implements clustering via Expectation Maximization
but return a clear partitioning of the data,
i.e.
- EMProjectedClustering() - Constructor for class moa.clusterers.outliers.AnyOut.util.EMProjectedClustering
-
- emptyBuffer(long, double) - Method in class moa.clusterers.clustree.Entry
-
Clear the buffer in this entry and return a copy.
- EMTopDownTreeBuilder - Class in moa.clusterers.outliers.AnyOut.util
-
- EMTopDownTreeBuilder() - Constructor for class moa.clusterers.outliers.AnyOut.util.EMTopDownTreeBuilder
-
- ENABLE_UNDO - Static variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel.PreprocessDefaults
-
- ENABLE_UNDO_KEY - Static variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel.PreprocessDefaults
-
- enableClassMerge - Variable in class moa.evaluation.CMM
-
enable/disable class merge (main feature of ground truth analysis)
- enableModelError - Variable in class moa.evaluation.CMM
-
enable/disable model error
when enabled errors that are caused by the underling cluster model will not be counted
- enablePreciseTiming() - Static method in class moa.core.TimingUtils
-
- enableRefresh() - Method in class moa.gui.experimentertab.ExpPreviewPanel
-
- enableRefresh() - Method in class moa.gui.PreviewPanel
-
- endIndexValidation(int) - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
- enforceMemoryLimit() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Checks if the memory limit is exceeded and if so prunes the classifiers in the ensemble.
- enforceMemoryLimit() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Checks if the memory limit is exceeded and if so prunes the classifiers in the ensemble.
- enforceTrackerLimit() - Method in class moa.classifiers.trees.EFDT
-
- enforceTrackerLimit() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- enforceTrackerLimit() - Method in class moa.classifiers.trees.HoeffdingTree
-
- ensemble - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- ensemble - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- ensemble - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- ensemble - Variable in class moa.classifiers.meta.ADOB
-
- ensemble - Variable in class moa.classifiers.meta.BOLE
-
- ensemble - Variable in class moa.classifiers.meta.DACC
-
Ensemble of classifiers
- ensemble - Variable in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- ensemble - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- ensemble - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- ensemble - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- ensemble - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- ensemble - Variable in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- ensemble - Variable in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- ensemble - Variable in class moa.classifiers.meta.LearnNSE
-
- ensemble - Variable in class moa.classifiers.meta.LeveragingBag
-
- ensemble - Variable in class moa.classifiers.meta.LimAttClassifier
-
- ensemble - Variable in class moa.classifiers.meta.OCBoost
-
- ensemble - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Ensemble classifiers.
- ensemble - Variable in class moa.classifiers.meta.OnlineSmoothBoost
-
- ensemble - Variable in class moa.classifiers.meta.OzaBag
-
- ensemble - Variable in class moa.classifiers.meta.OzaBagAdwin
-
- ensemble - Variable in class moa.classifiers.meta.OzaBagASHT
-
- ensemble - Variable in class moa.classifiers.meta.OzaBoost
-
- ensemble - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- ensemble - Variable in class moa.classifiers.meta.RandomRules
-
- ensemble - Variable in class moa.classifiers.meta.StreamingRandomPatches
-
- ensemble - Variable in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- ensemble - Variable in class moa.classifiers.multitarget.BasicMultiLabelLearner
-
- ensemble - Variable in class moa.classifiers.multitarget.BasicMultiTargetRegressor
-
- ensemble - Variable in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- ensemble - Variable in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- ensemble - Variable in class moa.clusterers.meta.EnsembleClustererAbstract
-
- ensemble - Variable in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTreeEnsemble
-
- ensembleAges - Variable in class moa.classifiers.meta.DACC
-
Age of classifiers (to compare with maturity age)
- EnsembleClustererAbstract - Class in moa.clusterers.meta
-
- EnsembleClustererAbstract() - Constructor for class moa.clusterers.meta.EnsembleClustererAbstract
-
- EnsembleClustererAbstract.EnsembleRunnable - Class in moa.clusterers.meta
-
- EnsembleDriftDetectionMethods - Class in moa.classifiers.core.driftdetection
-
Ensemble Drift detection method
- EnsembleDriftDetectionMethods() - Constructor for class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
-
- ensembleLearnerOption - Variable in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTreeEnsemble
-
- EnsembleRunnable(AbstractClusterer, Instance) - Constructor for class moa.clusterers.meta.EnsembleClustererAbstract.EnsembleRunnable
-
- ensembleSize - Variable in class moa.classifiers.meta.LearnNSE
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.ADOB
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.BOLE
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.LearnNSE
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.LeveragingBag
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.OCBoost
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.OnlineSmoothBoost
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.OzaBag
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.OzaBagAdwin
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.OzaBagASHT
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.OzaBoost
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.RandomRules
-
- ensembleSizeOption - Variable in class moa.classifiers.meta.StreamingRandomPatches
-
- ensembleSizeOption - Variable in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- ensembleSizeOption - Variable in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- ensembleSizeOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequentialCV
-
- ensembleWeights - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- ensembleWeights - Variable in class moa.classifiers.meta.DACC
-
Weights of classifiers
- ensembleWeights - Variable in class moa.classifiers.meta.LearnNSE
-
- ensembleWeights - Variable in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- ensembleWindows - Variable in class moa.classifiers.meta.DACC
-
Evaluation windows (recent classification errors)
- entropy(DoubleVector) - Method in class moa.classifiers.rules.RuleClassifier
-
- EntropyCollection - Class in moa.evaluation
-
- EntropyCollection() - Constructor for class moa.evaluation.EntropyCollection
-
- entropyOption - Variable in class moa.tasks.EvaluateClustering
-
- entropyOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- EntropyThreshold - Class in moa.classifiers.rules.multilabel.outputselectors
-
Entropy measure use by online multi-label AMRules for heuristics computation.
- EntropyThreshold() - Constructor for class moa.classifiers.rules.multilabel.outputselectors.EntropyThreshold
-
- Entry - Class in moa.clusterers.clustree
-
- Entry(int) - Constructor for class moa.clusterers.clustree.Entry
-
Constructor for the entry.
- Entry(int, ClusKernel, long) - Constructor for class moa.clusterers.clustree.Entry
-
Constructuctor that creates an Entry with an empty buffer
and the data given by the Kernel.
- Entry(int, ClusKernel, long, Entry, Node) - Constructor for class moa.clusterers.clustree.Entry
-
extended constructor with containerNode and parentEntry
- Entry(int, Node, long, Entry, Node) - Constructor for class moa.clusterers.clustree.Entry
-
Constructor that creates an Entry that points to the given
node.
- Entry(Entry) - Constructor for class moa.clusterers.clustree.Entry
-
Copy constructor.
- entryToString(int) - Method in class moa.evaluation.preview.LearningCurve
-
- entryToString(int) - Method in class moa.evaluation.preview.Preview
-
- entryToString(int) - Method in class moa.evaluation.preview.PreviewCollection
-
- entryToString(int) - Method in class moa.evaluation.preview.PreviewCollectionLearningCurveWrapper
-
- entryToString(int, int) - Method in class moa.evaluation.preview.PreviewCollection
-
- enumerateMeasures() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns an enumeration of the additional measure names.
- enumerateValues() - Method in class com.yahoo.labs.samoa.instances.Attribute
-
Returns an enumeration of all the attribute's values if the
attribute is nominal, null otherwise.
- epochs - Variable in class moa.classifiers.meta.DynamicWeightedMajority
-
- epsilon - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- epsilon - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- epsilon - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- EPSILON - Static variable in class moa.clusterers.clustree.ClusKernel
-
Numeric epsilon.
- epsilonOption - Variable in class moa.classifiers.functions.AdaGrad
-
- epsilonOption - Variable in class moa.clusterers.denstream.WithDBSCAN
-
- epsilonPrimeSEEDOption - Variable in class moa.classifiers.core.driftdetection.SEEDChangeDetector
-
- EPSLATEX - moa.gui.experimentertab.PlotTab.Terminal
-
- EPSLATEX - moa.tasks.Plot.Terminal
-
- eq(double, double) - Static method in class moa.core.Utils
-
Tests if a is equal to b.
- equals(Object) - Method in class moa.capabilities.Capabilities
-
- equals(Object) - Method in class moa.clusterers.dstream.DensityGrid
-
Overrides Object's method equals to declare that two DensityGrids are equal iff their
dimensions are the same and each of their corresponding coordinates are the same.
- equals(Object) - Method in class moa.clusterers.outliers.AbstractC.StreamObj
-
- equals(Object) - Method in class moa.clusterers.outliers.Angiulli.StreamObj
-
- equals(Object) - Method in class moa.clusterers.outliers.MCOD.MicroCluster
-
- equals(Object) - Method in class moa.clusterers.outliers.MCOD.StreamObj
-
- equals(Object) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.Outlier
-
- equals(Object) - Method in class moa.clusterers.outliers.SimpleCOD.StreamObj
-
- equals(Object) - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator.Score
-
- equals(Object) - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator.Score
-
- equals(Capabilities) - Method in class moa.capabilities.Capabilities
-
- equals(Capability) - Method in class moa.capabilities.Capabilities
-
- equalsPassesTest - Variable in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
-
- equivIndexSizeOption - Variable in class moa.classifiers.meta.ADACC
-
Threshold for concept equivalence
- ERR - Static variable in class moa.classifiers.lazy.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
-
The floating point error to tolerate in finding the widest
rectangular side.
- error - Variable in class moa.classifiers.meta.OzaBagASHT
-
- error - Variable in class moa.classifiers.rules.multilabel.core.voting.MultiLabelVote
-
- ERROR_MARGIN - Static variable in class moa.classifiers.trees.iadem.Iadem2
-
- errorBoundOption - Variable in class moa.classifiers.meta.BOLE
-
- ErrorChange - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- ErrorChange - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- errorEstimator - Variable in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- errorFunction(double) - Static method in class moa.core.Statistics
-
Returns the error function of the normal distribution.
- errorFunctionComplemented(double) - Static method in class moa.core.Statistics
-
Returns the complementary Error function of the normal distribution.
- errorM - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.LeafNode
-
- ErrorMeasurement - Class in moa.classifiers.rules.errormeasurers
-
Computes error measures with a fading factor
fadingErrorFactorOption - Fading factor
- ErrorMeasurement() - Constructor for class moa.classifiers.rules.errormeasurers.ErrorMeasurement
-
- errorMeasurer - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- errorMeasurer - Variable in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- errorMeasurer - Variable in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- errorMeasurerOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- errorMeasurerOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- errorMeasurerOption - Variable in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- errorMeasurerOption - Variable in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- errorP - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.LeafNode
-
- errorPrediction - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- errors - Variable in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
-
- errors - Variable in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- errorSum - Variable in class moa.classifiers.rules.functions.TargetMean
-
- ErrorWeightedVote - Interface in moa.classifiers.rules.core.voting
-
ErrorWeightedVote interface for weighted votes based on estimates of errors.
- ErrorWeightedVoteMultiLabel - Interface in moa.classifiers.rules.multilabel.core.voting
-
ErrorWeightedVoteMultiLabel interface for weighted votes based on estimates of errors.
- escribeFichero(String, String) - Static method in class moa.gui.experimentertab.statisticaltests.Fichero
-
- estimacionValorMedio() - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- estimador - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveNominalVirtualNode
-
- estimatedRemainingInstances() - Method in class moa.streams.ArffFileStream
-
- estimatedRemainingInstances() - Method in class moa.streams.BootstrappedStream
-
- estimatedRemainingInstances() - Method in class moa.streams.CachedInstancesStream
-
- estimatedRemainingInstances() - Method in class moa.streams.clustering.FileStream
-
- estimatedRemainingInstances() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- estimatedRemainingInstances() - Method in class moa.streams.clustering.SimpleCSVStream
-
- estimatedRemainingInstances() - Method in class moa.streams.ConceptDriftRealStream
-
- estimatedRemainingInstances() - Method in class moa.streams.ConceptDriftStream
-
- estimatedRemainingInstances() - Method in interface moa.streams.ExampleStream
-
Gets the estimated number of remaining instances in this stream
- estimatedRemainingInstances() - Method in class moa.streams.FilteredStream
-
- estimatedRemainingInstances() - Method in class moa.streams.filters.AbstractMultiLabelStreamFilter
-
- estimatedRemainingInstances() - Method in class moa.streams.filters.AbstractStreamFilter
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.AgrawalGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.AssetNegotiationGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.HyperplaneGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.LEDGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.MixedGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.RandomRBFGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.RandomTreeGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.SEAGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.SineGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.STAGGERGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.TextGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.generators.WaveformGenerator
-
- estimatedRemainingInstances() - Method in class moa.streams.ImbalancedStream
-
- estimatedRemainingInstances() - Method in class moa.streams.IrrelevantFeatureAppenderStream
-
- estimatedRemainingInstances() - Method in class moa.streams.MultiFilteredStream
-
- estimatedRemainingInstances() - Method in class moa.streams.MultiLabelFilteredStream
-
- estimatedRemainingInstances() - Method in class moa.streams.MultiTargetArffFileStream
-
- estimatedRemainingInstances() - Method in class moa.streams.PartitioningStream
-
- estimatedWeight_LessThan_EqualTo_GreaterThan_Value(double) - Method in class moa.core.GaussianEstimator
-
- estimateModelByteSizes() - Method in class moa.classifiers.trees.EFDT
-
- estimateModelByteSizes() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- estimateModelByteSizes() - Method in class moa.classifiers.trees.HoeffdingTree
-
- estimation - Variable in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Prediction for the next value based in previous seen values
- estimation - Variable in class moa.evaluation.EWMAClassificationPerformanceEvaluator.EWMAEstimator
-
- estimation - Variable in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator.FadingFactorEstimator
-
- estimation() - Method in class moa.evaluation.AdwinClassificationPerformanceEvaluator.AdwinEstimator
-
- estimation() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.SimpleEstimator
-
- estimation() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator.BasicEstimator
-
- estimation() - Method in interface moa.evaluation.BasicClassificationPerformanceEvaluator.Estimator
-
- estimation() - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator.EWMAEstimator
-
- estimation() - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator.FadingFactorEstimator
-
- estimation() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.SimpleEstimator
-
- estimation() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator.WindowEstimator
-
- estimationErrorWeight - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- estimationErrorWeight - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- estimator - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- estimator - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNode
-
- estimator - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveNumericVirtualNode
-
- estimator - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- Estimator(boolean) - Constructor for class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- Estimator(int) - Constructor for class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator.Estimator
-
- Estimator(int) - Constructor for class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator.Estimator
-
- Estimator(int) - Constructor for class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- Estimator(int) - Constructor for class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
-
- euclidean(DistanceFunctions.EuclideanCoordinate, DistanceFunctions.EuclideanCoordinate) - Static method in class moa.clusterers.outliers.utils.mtree.DistanceFunctions
-
- EUCLIDEAN - Static variable in class moa.clusterers.outliers.utils.mtree.DistanceFunctions
-
- EUCLIDEAN_DOUBLE_LIST - Static variable in class moa.clusterers.outliers.utils.mtree.DistanceFunctions
-
A
distance function object that calculates
the distance between two coordinates represented by lists of
Doubles.
- EUCLIDEAN_INTEGER_LIST - Static variable in class moa.clusterers.outliers.utils.mtree.DistanceFunctions
-
A
distance function object that calculates
the distance between two coordinates represented by lists of
Integers.
- EuclideanDistance - Class in moa.classifiers.lazy.neighboursearch
-
Implementing Euclidean distance (or similarity) function.
One object defines not one distance but the data model in which the distances between objects of that data model can be computed.
Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.
For more information, see:
Wikipedia.
- EuclideanDistance() - Constructor for class moa.classifiers.lazy.neighboursearch.EuclideanDistance
-
Constructs an Euclidean Distance object, Instances must be still set.
- EuclideanDistance(Instances) - Constructor for class moa.classifiers.lazy.neighboursearch.EuclideanDistance
-
Constructs an Euclidean Distance object and automatically initializes the
ranges.
- evalTaskOption - Variable in class moa.options.DependentOptionsUpdater
-
- evaluate(Instance) - Method in class moa.classifiers.rules.core.conditionaltests.NominalAttributeBinaryRulePredicate
-
- evaluate(Instance) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- evaluate(Instance) - Method in class moa.classifiers.rules.core.NominalRulePredicate
-
- evaluate(Instance) - Method in class moa.classifiers.rules.core.NumericRulePredicate
-
- evaluate(Instance) - Method in interface moa.classifiers.rules.core.Predicate
-
- evaluate(Instance) - Method in class moa.classifiers.rules.core.RuleSplitNode
-
- evaluate(Instance) - Method in class moa.classifiers.rules.multilabel.core.Literal
-
- evaluate(Instance) - Method in class moa.classifiers.rules.Predicates
-
- evaluate(MultiLabelInstance) - Method in class moa.classifiers.rules.core.NominalRulePredicate
-
- evaluate(MultiLabelInstance) - Method in class moa.classifiers.rules.core.NumericRulePredicate
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.Accuracy
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.ALMeasureCollection
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.ChangeDetectionMeasures
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.CMM
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.EntropyCollection
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.F1
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.General
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.MeasureCollection
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.OutlierPerformance
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.Separation
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.SilhouetteCoefficient
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.SSQ
-
- evaluateClustering(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.StatisticalCollection
-
- EvaluateClustering - Class in moa.tasks
-
Task for evaluating a clusterer on a stream.
- EvaluateClustering() - Constructor for class moa.tasks.EvaluateClustering
-
- evaluateClusteringPerformance(Clustering, Clustering, ArrayList<DataPoint>) - Method in class moa.evaluation.MeasureCollection
-
- EvaluateConceptDrift - Class in moa.gui.experimentertab.tasks
-
Task for evaluating a classifier on a stream by testing then training with each example in sequence.
- EvaluateConceptDrift - Class in moa.tasks
-
Task for evaluating a classifier on a stream by testing then training with each example in sequence.
- EvaluateConceptDrift() - Constructor for class moa.gui.experimentertab.tasks.EvaluateConceptDrift
-
- EvaluateConceptDrift() - Constructor for class moa.tasks.EvaluateConceptDrift
-
- EvaluateInterleavedChunks - Class in moa.gui.experimentertab.tasks
-
- EvaluateInterleavedChunks - Class in moa.tasks
-
- EvaluateInterleavedChunks() - Constructor for class moa.gui.experimentertab.tasks.EvaluateInterleavedChunks
-
- EvaluateInterleavedChunks() - Constructor for class moa.tasks.EvaluateInterleavedChunks
-
- EvaluateInterleavedTestThenTrain - Class in moa.gui.experimentertab.tasks
-
Task for evaluating a classifier on a stream by testing then training with
each example in sequence.
- EvaluateInterleavedTestThenTrain - Class in moa.tasks
-
Task for evaluating a classifier on a stream by testing then training with each example in sequence.
- EvaluateInterleavedTestThenTrain() - Constructor for class moa.gui.experimentertab.tasks.EvaluateInterleavedTestThenTrain
-
- EvaluateInterleavedTestThenTrain() - Constructor for class moa.tasks.EvaluateInterleavedTestThenTrain
-
- evaluateMicroClusteringOption - Variable in class moa.clusterers.AbstractClusterer
-
- EvaluateModel - Class in moa.tasks
-
Task for evaluating a static model on a stream.
- EvaluateModel() - Constructor for class moa.tasks.EvaluateModel
-
- EvaluateModel(Classifier, InstanceStream, LearningPerformanceEvaluator, int) - Constructor for class moa.tasks.EvaluateModel
-
- EvaluateModelMultiLabel - Class in moa.tasks
-
Task for evaluating a static model on a stream.
- EvaluateModelMultiLabel() - Constructor for class moa.tasks.EvaluateModelMultiLabel
-
- EvaluateModelMultiLabel(Classifier, InstanceStream, LearningPerformanceEvaluator, int) - Constructor for class moa.tasks.EvaluateModelMultiLabel
-
- EvaluateModelMultiTarget - Class in moa.tasks
-
Task for evaluating a static model on a stream.
- EvaluateModelMultiTarget() - Constructor for class moa.tasks.EvaluateModelMultiTarget
-
- EvaluateModelMultiTarget(Classifier, InstanceStream, LearningPerformanceEvaluator, int) - Constructor for class moa.tasks.EvaluateModelMultiTarget
-
- EvaluateModelRegression - Class in moa.tasks
-
Task for evaluating a static model on a stream.
- EvaluateModelRegression() - Constructor for class moa.tasks.EvaluateModelRegression
-
- EvaluateModelRegression(Classifier, InstanceStream, LearningPerformanceEvaluator, int) - Constructor for class moa.tasks.EvaluateModelRegression
-
- EvaluateMultipleClusterings - Class in moa.tasks
-
Task for evaluating a clusterer on multiple (related) streams.
- EvaluateMultipleClusterings() - Constructor for class moa.tasks.EvaluateMultipleClusterings
-
- EvaluateOnlineRecommender - Class in moa.tasks
-
Test for evaluating a recommender by training and periodically testing
on samples from a rating dataset.
- EvaluateOnlineRecommender() - Constructor for class moa.tasks.EvaluateOnlineRecommender
-
- evaluateOption - Variable in class moa.clusterers.streamkm.StreamKM
-
- evaluatePerformance() - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- EvaluatePeriodicHeldOutTest - Class in moa.gui.experimentertab.tasks
-
Task for evaluating a classifier on a stream by periodically testing on a
heldout set.
- EvaluatePeriodicHeldOutTest - Class in moa.tasks
-
Task for evaluating a classifier on a stream by periodically testing on a heldout set.
- EvaluatePeriodicHeldOutTest() - Constructor for class moa.gui.experimentertab.tasks.EvaluatePeriodicHeldOutTest
-
- EvaluatePeriodicHeldOutTest() - Constructor for class moa.tasks.EvaluatePeriodicHeldOutTest
-
- EvaluatePrequential - Class in moa.gui.experimentertab.tasks
-
- EvaluatePrequential - Class in moa.tasks
-
Task for evaluating a classifier on a stream by testing then training with each example in sequence.
- EvaluatePrequential() - Constructor for class moa.gui.experimentertab.tasks.EvaluatePrequential
-
- EvaluatePrequential() - Constructor for class moa.tasks.EvaluatePrequential
-
- EvaluatePrequentialCV - Class in moa.gui.experimentertab.tasks
-
Task for prequential cross-validation evaluation of a classifier on a stream by testing then training with each
example in sequence and doing cross-validation at the same time.
- EvaluatePrequentialCV - Class in moa.tasks
-
Task for prequential cross-validation evaluation of a classifier on a stream by testing then training with each
example in sequence and doing cross-validation at the same time.
- EvaluatePrequentialCV() - Constructor for class moa.gui.experimentertab.tasks.EvaluatePrequentialCV
-
- EvaluatePrequentialCV() - Constructor for class moa.tasks.EvaluatePrequentialCV
-
- EvaluatePrequentialDelayed - Class in moa.tasks
-
Task for evaluating a classifier on a delayed stream by testing and only
training with the example after k other examples (delayed labeling).
- EvaluatePrequentialDelayed() - Constructor for class moa.tasks.EvaluatePrequentialDelayed
-
- EvaluatePrequentialDelayedCV - Class in moa.tasks
-
Task for delayed cross-validation evaluation of a classifier on a
stream by testing and only training with the example after the arrival of
other k examples (delayed labeling).
- EvaluatePrequentialDelayedCV() - Constructor for class moa.tasks.EvaluatePrequentialDelayedCV
-
- EvaluatePrequentialMultiLabel - Class in moa.tasks
-
Task for evaluating a classifier on a stream by testing then training with each example in sequence.
- EvaluatePrequentialMultiLabel() - Constructor for class moa.tasks.EvaluatePrequentialMultiLabel
-
- EvaluatePrequentialMultiTarget - Class in moa.tasks
-
Task for evaluating a classifier on a stream by testing then training with each example in sequence.
- EvaluatePrequentialMultiTarget() - Constructor for class moa.tasks.EvaluatePrequentialMultiTarget
-
- EvaluatePrequentialMultiTargetSemiSuper - Class in moa.tasks
-
Multi-target Prequential semi-supervised evaluation
Phase1: Creates a initial model with of the instances in the dataset
Phase2: When an instance is received:
A binary random process with a binomial distribution selects if the instance should be
labeled or unlabeled with probability .
- EvaluatePrequentialMultiTargetSemiSuper() - Constructor for class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- EvaluatePrequentialRegression - Class in moa.tasks
-
Task for evaluating a classifier on a stream by testing then training with each example in sequence.
- EvaluatePrequentialRegression() - Constructor for class moa.tasks.EvaluatePrequentialRegression
-
- evaluationFrequencyOption - Variable in class moa.streams.clustering.ClusteringStream
-
- evaluationSizeOption - Variable in class moa.classifiers.meta.DACC
-
Size of the evaluation window for weights computing
- evaluator - Variable in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- evaluator - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- evaluator - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- evaluator - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- evaluator - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- evaluatorOption - Variable in class moa.gui.experimentertab.tasks.EvaluateConceptDrift
-
- evaluatorOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedChunks
-
Allows to select the classifier performance evaluation method.
- evaluatorOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedTestThenTrain
-
- evaluatorOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePeriodicHeldOutTest
-
- evaluatorOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequential
-
- evaluatorOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequentialCV
-
- evaluatorOption - Variable in class moa.tasks.EvaluateConceptDrift
-
- evaluatorOption - Variable in class moa.tasks.EvaluateInterleavedChunks
-
Allows to select the classifier performance evaluation method.
- evaluatorOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- evaluatorOption - Variable in class moa.tasks.EvaluateModel
-
- evaluatorOption - Variable in class moa.tasks.EvaluateModelMultiLabel
-
- evaluatorOption - Variable in class moa.tasks.EvaluateModelMultiTarget
-
- evaluatorOption - Variable in class moa.tasks.EvaluateModelRegression
-
- evaluatorOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
-
- evaluatorOption - Variable in class moa.tasks.EvaluatePrequential
-
- evaluatorOption - Variable in class moa.tasks.EvaluatePrequentialCV
-
- evaluatorOption - Variable in class moa.tasks.EvaluatePrequentialDelayed
-
- evaluatorOption - Variable in class moa.tasks.EvaluatePrequentialDelayedCV
-
- evaluatorOption - Variable in class moa.tasks.EvaluatePrequentialMultiLabel
-
- evaluatorOption - Variable in class moa.tasks.EvaluatePrequentialMultiTarget
-
- evaluatorOption - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- evaluatorOption - Variable in class moa.tasks.EvaluatePrequentialRegression
-
- evaluatorOption - Variable in class moa.tasks.meta.ALPrequentialEvaluationTask
-
- eventDeleteCreateOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- eventFrequencyOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- EventItem(ISBIndex.ISBNode, Long) - Constructor for class moa.clusterers.outliers.MCOD.MCODBase.EventItem
-
- EventItem(ISBIndex.ISBNode, Long) - Constructor for class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventItem
-
- eventMergeSplitOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- eventQueue - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- eventQueue - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- EventQueue() - Constructor for class moa.clusterers.outliers.MCOD.MCODBase.EventQueue
-
- EventQueue() - Constructor for class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventQueue
-
- events - Variable in class moa.gui.experimentertab.tasks.ConceptDriftMainTask
-
- events - Variable in class moa.tasks.AuxiliarMainTask
-
- events - Variable in class moa.tasks.ClassificationMainTask
-
- events - Variable in class moa.tasks.ConceptDriftMainTask
-
- events - Variable in class moa.tasks.MultiLabelMainTask
-
- events - Variable in class moa.tasks.MultiTargetMainTask
-
- events - Variable in class moa.tasks.RegressionMainTask
-
- EWMA_Estimator - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test.SampleInfo
-
- EWMAChartDM - Class in moa.classifiers.core.driftdetection
-
Drift detection method based in EWMA Charts of Ross, Adams, Tasoulis and Hand
2012
- EWMAChartDM() - Constructor for class moa.classifiers.core.driftdetection.EWMAChartDM
-
- EWMAClassificationPerformanceEvaluator - Class in moa.evaluation
-
Classification evaluator that updates evaluation results using an Exponential Weighted Moving Average.
- EWMAClassificationPerformanceEvaluator() - Constructor for class moa.evaluation.EWMAClassificationPerformanceEvaluator
-
- EWMAClassificationPerformanceEvaluator.EWMAEstimator - Class in moa.evaluation
-
- EWMAEstimator(double) - Constructor for class moa.evaluation.EWMAClassificationPerformanceEvaluator.EWMAEstimator
-
- ExactSTORM - Class in moa.clusterers.outliers.Angiulli
-
- ExactSTORM() - Constructor for class moa.clusterers.outliers.Angiulli.ExactSTORM
-
- ExactSTORM.ISBNodeExact - Class in moa.clusterers.outliers.Angiulli
-
- Example<T> - Interface in moa.core
-
- examplesSeen - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- examplesSeen - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- examplesSeen - Variable in class moa.classifiers.trees.ARFFIMTDD.Node
-
- examplesSeen - Variable in class moa.classifiers.trees.FIMTDD
-
- examplesSeen - Variable in class moa.classifiers.trees.FIMTDD.Node
-
- examplesSeenAtLastSplitEvaluation - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.LeafNode
-
- examplesSeenAtLastSplitEvaluation - Variable in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- examplesSeenAtLastSplitEvaluation - Variable in class moa.classifiers.trees.FIMTDD.LeafNode
-
- ExampleStream<E extends Example> - Interface in moa.streams
-
Interface representing a data stream of examples.
- executor - Variable in class moa.clusterers.meta.EnsembleClustererAbstract
-
- expandedLearningLiteral - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- expandeRule(RuleClassification, Instance, int) - Method in class moa.classifiers.rules.RuleClassifier
-
- expectedType - Variable in class com.github.javacliparser.ListOption
-
- ExperimenterTabPanel - Class in moa.gui.experimentertab
-
- ExperimenterTabPanel() - Constructor for class moa.gui.experimentertab.ExperimenterTabPanel
-
Initializes the different tabs of the application
- ExperimenterTask - Class in moa.gui.experimentertab.tasks
-
- ExperimenterTask() - Constructor for class moa.gui.experimentertab.tasks.ExperimenterTask
-
- ExperimeterCLI - Class in moa.gui.experimentertab
-
- ExperimeterCLI(String[]) - Constructor for class moa.gui.experimentertab.ExperimeterCLI
-
- experts - Variable in class moa.classifiers.meta.DynamicWeightedMajority
-
- ExpNegErrorWeightedVote - Class in moa.classifiers.rules.core.voting
-
ExpNegErrorWeightedVote class for weighted votes based on estimates of errors.
- ExpNegErrorWeightedVote() - Constructor for class moa.classifiers.rules.core.voting.ExpNegErrorWeightedVote
-
- exponential(double[]) - Method in class moa.classifiers.rules.RuleClassifierNBayes
-
- exportAdvancedNotebook - Variable in class moa.tasks.WriteConfigurationToJupyterNotebook
-
- exportButton - Variable in class moa.gui.experimentertab.TaskTextViewerPanel
-
- exportButton - Variable in class moa.gui.TaskTextViewerPanel
-
- exportButton - Variable in class moa.gui.TextViewerPanel
-
- exportCSV(String) - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- exportCSV(String) - Method in class moa.gui.visualization.RunVisualizer
-
- exportCSV(String, ArrayList<ClusterEvent>, MeasureCollection[], int) - Static method in class moa.gui.BatchCmd
-
- exportFileExtension - Static variable in class moa.gui.active.ALTaskManagerPanel
-
- exportFileExtension - Static variable in class moa.gui.AuxiliarTaskManagerPanel
-
- exportFileExtension - Static variable in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- exportFileExtension - Static variable in class moa.gui.experimentertab.TaskTextViewerPanel
-
- exportFileExtension - Static variable in class moa.gui.MultiLabelTaskManagerPanel
-
- exportFileExtension - Static variable in class moa.gui.MultiTargetTaskManagerPanel
-
- exportFileExtension - Static variable in class moa.gui.RegressionTaskManagerPanel
-
- exportFileExtension - Static variable in class moa.gui.TaskManagerPanel
-
- exportFileExtension - Static variable in class moa.gui.TaskTextViewerPanel
-
- exportFileExtension - Static variable in class moa.gui.TextViewerPanel
-
- exportIMG(String, String) - Method in class moa.gui.experimentertab.ImageChart
-
Export the image to formats JPG, PNG, SVG and EPS.
- ExpPreviewPanel - Class in moa.gui.experimentertab
-
This panel displays the running task preview text and buttons.
- ExpPreviewPanel() - Constructor for class moa.gui.experimentertab.ExpPreviewPanel
-
- ExpPreviewPanel(ExpPreviewPanel.TypePanel) - Constructor for class moa.gui.experimentertab.ExpPreviewPanel
-
- ExpPreviewPanel(ExpPreviewPanel.TypePanel, CDTaskManagerPanel) - Constructor for class moa.gui.experimentertab.ExpPreviewPanel
-
- ExpPreviewPanel.TypePanel - Enum in moa.gui.experimentertab
-
- ExpTaskThread - Class in moa.gui.experimentertab
-
Task Thread.
- ExpTaskThread(Buffer) - Constructor for class moa.gui.experimentertab.ExpTaskThread
-
- ExpTaskThread.Status - Enum in moa.gui.experimentertab
-
- extendWithOldLabels(Instance) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
-
- ExtractMin() - Method in class moa.clusterers.outliers.MCOD.MCODBase.EventQueue
-
- ExtractMin() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventQueue
-
- g - Variable in class moa.core.GreenwaldKhannaQuantileSummary.Tuple
-
- gamma - Variable in class moa.classifiers.meta.OnlineSmoothBoost
-
- gamma(double) - Static method in class moa.core.Statistics
-
Returns the Gamma function of the argument.
- gammaOption - Variable in class moa.classifiers.meta.OnlineSmoothBoost
-
- gammaOption - Variable in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- GaussianEstimator - Class in moa.core
-
Gaussian incremental estimator that uses incremental method that is more resistant to floating point imprecision.
- GaussianEstimator() - Constructor for class moa.core.GaussianEstimator
-
- gaussianMeans(Clustering, Clustering) - Static method in class moa.clusterers.KMeans
-
- GaussianNumericAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers
-
Class for observing the class data distribution for a numeric attribute using gaussian estimators.
- GaussianNumericAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- GaussInequality - Class in moa.classifiers.rules.core.anomalydetection.probabilityfunctions
-
Returns the probability for anomaly detection according to a Gauss inequality
mean- mean of a data variable
sd- standard deviation of a data variable
value- current value of the variable
- GaussInequality() - Constructor for class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.GaussInequality
-
- gb - Variable in class moa.gui.experimentertab.RankingGraph
-
- General - Class in moa.evaluation
-
- General() - Constructor for class moa.evaluation.General
-
- generalEvalOption - Variable in class moa.tasks.EvaluateClustering
-
- generalEvalOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- generateCentroids() - Method in class moa.streams.generators.RandomRBFGenerator
-
- generateCentroids() - Method in class moa.streams.generators.RandomRBFGeneratorDrift
-
- generateColors(int) - Method in interface moa.gui.colorGenerator.ColorGenerator
-
Generate numColors unique colors which should be easily distinguishable.
- generateColors(int) - Method in class moa.gui.colorGenerator.HSVColorGenerator
-
Generate numColors unique colors which should be easily distinguishable.
- generateConditional(double[], boolean[][]) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
GenerateConditional.
- generateCSV() - Method in class moa.gui.experimentertab.Summary
-
Generate a csv file for the statistical analysis.
- generateExample() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Generates one example of the dataset.
- generateExamples() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Generates all examples of the dataset.
- generateFinished() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Generates a comment string that documentats the data generator.
- generateHeader() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- generateHeader() - Method in class moa.streams.generators.HyperplaneGenerator
-
- generateHeader() - Method in class moa.streams.generators.RandomRBFGenerator
-
- generateHeader() - Method in class moa.streams.generators.RandomTreeGenerator
-
- generateHTML(String) - Method in class moa.gui.experimentertab.Summary
-
Generates an HTML summary, in which the rows are the datasets and the
columns the algorithms.
- generatekMeansPlusPlusCentroids(int, List<double[]>, Random) - Static method in class moa.clusterers.kmeanspm.CoresetKMeans
-
Generates the initial centroids like the k-means++ algorithm.
- generateLatex(String) - Method in class moa.gui.experimentertab.Summary
-
Generates a latex summary, in which the rows are the algorithms and the
columns the datasets.
- generateMultilabelHeader(Instances) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
GenerateMultilabelHeader.
- generateNewConfigurations() - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- generateOptionsString() - Method in class moa.tasks.ipynb.OptionsString
-
- generateRandomTree() - Method in class moa.streams.generators.RandomTreeGenerator
-
- generateRandomTreeNode(int, ArrayList<Integer>, double[], double[], Random) - Method in class moa.streams.generators.RandomTreeGenerator
-
- generateSizeOption - Variable in class moa.tasks.MeasureStreamSpeed
-
- generateStart() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Generates a comment string that documentates the data generator.
- generatorTipText() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Returns the tooltip displayed in the GUI.
- GeometricMovingAverageDM - Class in moa.classifiers.core.driftdetection
-
Drift detection method based in Geometric Moving Average Test
- GeometricMovingAverageDM() - Constructor for class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
-
- get() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap
-
returns the first element and removes it from the heap.
- get(int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
- get(int) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- get(int) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Reservoir
-
- get(int) - Method in class moa.cluster.Clustering
-
get a cluster from the clustering
- get(int) - Method in class moa.clusterers.outliers.AbstractC.StreamObj
-
- get(int) - Method in class moa.clusterers.outliers.Angiulli.StreamObj
-
- get(int) - Method in class moa.clusterers.outliers.MCOD.MicroCluster
-
- get(int) - Method in class moa.clusterers.outliers.MCOD.StreamObj
-
- get(int) - Method in class moa.clusterers.outliers.SimpleCOD.StreamObj
-
- get(int) - Method in interface moa.clusterers.outliers.utils.mtree.DistanceFunctions.EuclideanCoordinate
-
A method to access the index-th component of the coordinate.
- get(int) - Method in class moa.clusterers.outliers.utils.mtree.utils.Pair
-
Accesses an object by its index.
- get(int) - Method in class moa.core.AutoExpandVector
-
- get(int) - Method in class moa.recommender.rc.utils.DenseVector
-
- get(int) - Method in class moa.recommender.rc.utils.SparseVector
-
- get(int) - Method in class moa.recommender.rc.utils.Vector
-
- get(long) - Method in class moa.clusterers.kmeanspm.CuckooHashing
-
Gets an element of the hash table.
- get(String, String) - Static method in class moa.gui.GUIDefaults
-
returns the value for the specified property, if non-existent then the
default value.
- Get_nn_before() - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- Get_nn_before() - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- getAbsNumOfAcqInst() - Method in class moa.evaluation.ALWindowClassificationPerformanceEvaluator
-
Returns absolute number of acquired labels so far.
- getAccumulated() - Method in class moa.classifiers.rules.featureranking.MeritFeatureRanking
-
- getAccumulated() - Method in class moa.classifiers.rules.featureranking.MeritFeatureRanking.RuleInformation
-
- getAccumulatedMerit() - Method in class moa.classifiers.rules.featureranking.BasicFeatureRanking.RuleInformation
-
- getAccuracy() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- getAccuracy() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- getActiveXDim() - Method in class moa.gui.visualization.StreamOutlierPanel
-
- getActiveXDim() - Method in class moa.gui.visualization.StreamPanel
-
- getActiveYDim() - Method in class moa.gui.visualization.StreamOutlierPanel
-
- getActiveYDim() - Method in class moa.gui.visualization.StreamPanel
-
- getAcuity() - Method in class moa.clusterers.CobWeb
-
get the acuity value
- getAlgNames() - Method in class moa.gui.experimentertab.ReadFile
-
Returns the name of the algorithms.
- getAlgorithm() - Method in class moa.gui.experimentertab.Stream
-
Returns the list of the algorithms
- getAlgorithm0ValueAsCLIString() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- getAlgorithm0ValueAsCLIString() - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- getAlgorithm1ValueAsCLIString() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- getAlgorithm1ValueAsCLIString() - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- getAlgorithms() - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- getAlgorithmsID() - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- getAlgShortNames() - Method in class moa.gui.experimentertab.ReadFile
-
Returns the short name of the algorithms.
- getAllClassNames() - Static method in class moa.core.AutoClassDiscovery
-
Returns all class names stored in the cache.
- getAllValues(int) - Method in class moa.evaluation.MeasureCollection
-
- getAMRules() - Method in class moa.classifiers.rules.core.Rule.Builder
-
- getAnomalyScore() - Method in class moa.classifiers.rules.core.anomalydetection.AnomalinessRatioScore
-
- getAnomalyScore() - Method in interface moa.classifiers.rules.core.anomalydetection.AnomalyDetector
-
- getAnomalyScore() - Method in class moa.classifiers.rules.core.anomalydetection.NoAnomalyDetection
-
- getAnomalyScore() - Method in class moa.classifiers.rules.core.anomalydetection.OddsRatioScore
-
- getAnomalyScore() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getAnomalyScore(Instance) - Method in class moa.classifiers.oneclass.Autoencoder
-
Returns the squared error between the input value and the reconstructed value as
the anomaly score for the argument instance.
- getAnomalyScore(Instance) - Method in class moa.classifiers.oneclass.HSTrees
-
Returns the anomaly score for the argument instance.
- getAnomalyScore(Instance) - Method in class moa.classifiers.oneclass.NearestNeighbourDescription
-
Returns the anomaly score for an argument instance based on the distance from it to its nearest neighbour compared
to the distance from its nearest neighbour to the neighbour's nearest neighbour.
- getAnomalyScore(Instance) - Method in interface moa.classifiers.OneClassClassifier
-
For use when an anomaly score is needed instead of a vote.
- getArgs() - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- getArrayClass(Class) - Static method in class moa.core.Utils
-
Returns the basic class of an array class (handles multi-dimensional
arrays).
- getArrayCopy() - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- getArrayCopy() - Method in class moa.core.DoubleVector
-
- getArrayDimensions(Class) - Static method in class moa.core.Utils
-
Returns the dimensions of the given array.
- getArrayDimensions(Object) - Static method in class moa.core.Utils
-
Returns the dimensions of the given array.
- getArrayRef() - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- getArrayRef() - Method in class moa.core.DoubleVector
-
- getAsCLIString() - Method in class com.github.javacliparser.Options
-
- getAttIndex() - Method in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- getAttribute() - Method in class moa.clusterers.dstream.CharacteristicVector
-
- getAttributeDifferentiation() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getAttributeImportance(int) - Method in class moa.classifiers.rules.featureranking.WeightedMajorityFeatureRanking.RuleInformation
-
- getAttributeIndex() - Method in class moa.classifiers.rules.core.conditionaltests.NominalAttributeBinaryRulePredicate
-
- getAttributeIndex() - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- getAttributeIndex() - Method in class moa.classifiers.rules.core.NominalRulePredicate
-
- getAttributeIndex() - Method in class moa.classifiers.rules.core.NumericRulePredicate
-
- getAttributeIndex() - Method in interface moa.classifiers.rules.core.Predicate
-
- getAttributeIndex() - Method in class moa.classifiers.rules.featureranking.messages.RuleExpandedMessage
-
- getAttributeIndex() - Method in class moa.classifiers.rules.multilabel.core.Literal
-
- getAttributeIndex() - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- getAttributeIndices() - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction
-
Gets the range of attributes used in the calculation of the distance.
- getAttributeIndices() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Gets the range of attributes used in the calculation of the distance.
- getAttributeMask() - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getAttributeName() - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- getAttributeNameString(int) - Method in class moa.classifiers.AbstractClassifier
-
Gets the name of an attribute from the header.
- getAttributeNameString(int) - Method in class moa.clusterers.AbstractClusterer
-
- getAttributeNameString(InstancesHeader, int) - Static method in class com.yahoo.labs.samoa.instances.InstancesHeader
-
- getAttributeObservers() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getAttributesImportance() - Method in class moa.classifiers.rules.featureranking.WeightedMajorityFeatureRanking.RuleInformation
-
- getAttributesPercentage() - Method in class moa.classifiers.rules.AbstractAMRules
-
- getAttributesPercentage() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- getAttributesPercentage() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- getAttributeValue() - Method in class moa.classifiers.rules.Predicates
-
- getAttributeValues() - Method in class com.yahoo.labs.samoa.instances.Attribute
-
Gets the attribute values.
- getAttributeValues() - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Gets the attribute values.
- getAttsTestDependsOn() - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalTest
-
Returns an array with the attributes that the test depends on.
- getAttsTestDependsOn() - Method in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
-
- getAttsTestDependsOn() - Method in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
-
- getAttsTestDependsOn() - Method in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
-
- getAttsTestDependsOn() - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- getAttValue() - Method in class moa.classifiers.trees.iadem.IademNominalAttributeBinaryTest
-
- getAUC() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- getAUC() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- getAucEstimator() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator
-
- getAucEstimator() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator
-
- getAverageInputs() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- getAverageInputs() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- getAverageOutputs() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- getAverageOutputs() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- getAvgRatingItem(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getAvgRatingItem(int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- getAvgRatingUser(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getAvgRatingUser(int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- getAWTRenderer() - Method in class moa.classifiers.AbstractClassifier
-
Returns the AWT Renderer
- getAWTRenderer() - Method in class moa.clusterers.AbstractClusterer
-
- getAWTRenderer() - Method in interface moa.gui.AWTRenderable
-
- getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in interface moa.classifiers.core.attributeclassobservers.AttributeClassObserver
-
Gets the best split suggestion given a criterion and a class distribution
- getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
-
- getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
-
- getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
-
- getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
-
- getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
-
- getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
-
- getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
-
- getBestEvaluatedSplitSuggestion(SplitCriterion, double[], int, boolean) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- getBestEvaluatedSplitSuggestion(MultiLabelSplitCriterion, DoubleVector[], int) - Method in interface moa.classifiers.rules.multilabel.attributeclassobservers.AttributeStatisticsObserver
-
Gets the best split suggestion given a criterion and a class distribution
- getBestEvaluatedSplitSuggestion(MultiLabelSplitCriterion, DoubleVector[], int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- getBestEvaluatedSplitSuggestion(MultiLabelSplitCriterion, DoubleVector[], int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- getBestEvaluatedSplitSuggestion(MultiLabelSplitCriterion, DoubleVector[], int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelNominalAttributeObserver
-
- getBestSecondBestEntropy(DoubleVector) - Method in class moa.classifiers.rules.RuleClassifier
-
- getBestSplitSuggestion() - Method in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- getBestSplitSuggestion(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getBestSplitSuggestionIADEM(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getBestSplitSuggestions(SplitCriterion) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- getBestSplitSuggestions(SplitCriterion) - Method in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
Return the best split suggestions for this node using the given split criteria
- getBestSplitSuggestions(SplitCriterion) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
-
Return the best split suggestions for this node using the given split criteria
- getBestSplitSuggestions(SplitCriterion, EFDT) - Method in class moa.classifiers.trees.EFDT.ActiveLearningNode
-
- getBestSplitSuggestions(SplitCriterion, EFDT) - Method in class moa.classifiers.trees.EFDT.EFDTSplitNode
-
- getBestSplitSuggestions(SplitCriterion, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
-
- getBestSplitSuggestions(SplitCriterion, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
-
- getBestSplitSuggestions(MultiLabelSplitCriterion) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.LeafNode
-
Return the best split suggestions for this node using the given split criteria
- getBestSuggestion() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getBestSuggestion() - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getBlockCount() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- getBlockSize() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- getBlockSize() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- getBranchesSplitMerits(DoubleVector[][]) - Method in class moa.classifiers.multilabel.core.splitcriteria.ICVarianceReduction
-
- getBranchesSplitMerits(DoubleVector[][]) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultilabelInformationGain
-
- getBranchesSplitMerits(DoubleVector[][]) - Method in interface moa.classifiers.rules.multilabel.core.splitcriteria.MultiLabelSplitCriterion
-
- getBranchesSplitMerits(DoubleVector[][]) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultiTargetVarianceRatio
-
- getBranchSplitEntropyOutput(DoubleVector[]) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultilabelInformationGain
-
- getBranchSplitVarianceOutput(DoubleVector[]) - Method in class moa.classifiers.multilabel.core.splitcriteria.ICVarianceReduction
-
- getBranchSplitVarianceOutput(DoubleVector[]) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultiTargetVarianceRatio
-
- getBucketsUsed() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getBuffer() - Method in class moa.clusterers.clustree.Entry
-
Getter for the buffer.
- getBuilder() - Method in class moa.classifiers.rules.core.Rule
-
- getBytesRead() - Method in class moa.core.InputStreamProgressMonitor
-
- getBytesRemaining() - Method in class moa.core.InputStreamProgressMonitor
-
- getCapabilities() - Method in interface moa.capabilities.CapabilitiesHandler
-
Gets the capabilities of the object.
- getCapabilities() - Method in class weka.classifiers.meta.MOA
-
Returns the Capabilities of this classifier.
- getCellByIndex(int) - Method in class moa.tasks.ipynb.NotebookBuilder
-
- getCenter() - Method in class moa.cluster.CFCluster
-
- getCenter() - Method in class moa.cluster.Cluster
-
- getCenter() - Method in class moa.cluster.SphereCluster
-
- getCenter() - Method in class moa.clusterers.clustream.ClustreamKernel
-
- getCenter() - Method in class moa.clusterers.clustree.ClusKernel
-
- getCenter() - Method in class moa.clusterers.denstream.MicroCluster
-
- getCenter() - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Gets the representation of the ClusteringFeature
- getCenterDistance(Instance) - Method in class moa.cluster.SphereCluster
-
- getCenterDistance(SphereCluster) - Method in class moa.cluster.SphereCluster
-
- getCF() - Method in class moa.cluster.CFCluster
-
- getCF() - Method in class moa.clusterers.clustream.ClustreamKernel
-
- getCF() - Method in class moa.clusterers.clustree.ClusKernel
-
- getCF() - Method in class moa.clusterers.denstream.MicroCluster
-
- getCF() - Method in class moa.clusterers.dstream.DensityGrid
-
Returns a reference to the DensityGrid.
- getCF() - Method in class moa.clusterers.macro.NonConvexCluster
-
- getCFCluster() - Method in class moa.clusterers.macro.dbscan.DenseMicroCluster
-
- getChange() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Gets whether there is change detected.
- getChange() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getChange() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector
-
Gets whether there is change detected.
- getChange() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- getChangedTrees() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- getChangeListener() - Method in class moa.options.ClassOptionWithListenerOption
-
- getChart() - Method in class moa.gui.experimentertab.ImageChart
-
Return the chart.
- getChart() - Method in class moa.gui.experimentertab.ImageTreePanel
-
Return the ImageChart array.
- getChild() - Method in class moa.clusterers.clustree.Entry
-
Return the reference to the child of this Entry to navigate
in the tree.
- getChild(int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- getChild(int) - Method in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- getChild(int) - Method in class moa.classifiers.trees.EFDT.SplitNode
-
- getChild(int) - Method in class moa.classifiers.trees.FIMTDD.InnerNode
-
- getChild(int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- getChild(int) - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- getChild(int) - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- getChildCount() - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- getChildCount() - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- getChildIndex(ISOUPTree.Node) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- getChildIndex(ISOUPTree.Node) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- getChildIndex(ARFFIMTDD.Node) - Method in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- getChildIndex(ARFFIMTDD.Node) - Method in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- getChildIndex(ARFFIMTDD.Node) - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- getChildIndex(FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.InnerNode
-
- getChildIndex(FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
-
- getChildIndex(FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.Node
-
- getChildren() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- getChildren() - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Gets a List of the children nodes.
- getChosenIndex() - Method in class com.github.javacliparser.MultiChoiceOption
-
- getChosenLabel() - Method in class com.github.javacliparser.MultiChoiceOption
-
- getChosenObjectCLIString(Class<?>) - Method in class moa.gui.ClassOptionSelectionPanel
-
- getChosenObjectCLIString(Class<?>) - Method in class moa.gui.ClassOptionWithNamesSelectionPanel
-
- getClassDist() - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- getClassDist() - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- getClassDist() - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- getClassDist() - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- getClassDistribution(int) - Method in class moa.evaluation.MembershipMatrix
-
- getClassDistributionAtTimeOfCreation() - Method in class moa.classifiers.trees.EFDT.Node
-
- getClassDistributionByLabel(int) - Method in class moa.evaluation.MembershipMatrix
-
- getClassDistsResultingFromBinarySplit(double) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- getClassDistsResultingFromBinarySplit(double) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
-
- getClassDistsResultingFromBinarySplit(int) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
-
- getClassDistsResultingFromMultiwaySplit(int) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
-
- getClassFullName() - Method in class moa.tasks.ipynb.OptionsString
-
- getClassifier() - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
-
- getClassifier() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTreeClassifLeaves.LearningNodeHATClassifier
-
- getClassifier() - Method in class moa.classifiers.trees.HoeffdingTreeClassifLeaves.LearningNodeClassifier
-
- getClassifier() - Method in class weka.classifiers.meta.MOA
-
Returns the current MOA classifier in use.
- getClassLabel() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
-
Return the label for the DataObject.
- getClassLabelString(int) - Method in class moa.classifiers.AbstractClassifier
-
Gets the name of a label of the class from the header.
- getClassLabelString(int) - Method in class moa.clusterers.AbstractClusterer
-
- getClassLabelString(InstancesHeader, int) - Static method in class com.yahoo.labs.samoa.instances.InstancesHeader
-
- getClassNames() - Method in class moa.options.ClassOptionWithNames
-
- getClassNameString() - Method in class moa.classifiers.AbstractClassifier
-
Gets the name of the attribute of the class from the header.
- getClassNameString() - Method in class moa.clusterers.AbstractClusterer
-
- getClassNameString(InstancesHeader) - Static method in class com.yahoo.labs.samoa.instances.InstancesHeader
-
- getClassSeparability() - Method in class moa.evaluation.CMM_GTAnalysis
-
Calculates how well the original clusters are separable.
- getClassShortName() - Method in class moa.tasks.ipynb.OptionsString
-
- getClassSum(int) - Method in class moa.evaluation.MembershipMatrix
-
- getClassSumByLabel(int) - Method in class moa.evaluation.MembershipMatrix
-
- getClassValueDist() - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNodeNB
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNodeNBKirkby
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNodeWeightedVote
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNB
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNBAdaptive
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNBKirkby
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeWeightedVote
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- getClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem3
-
- getClassVotes(Instance, EFDT) - Method in class moa.classifiers.trees.EFDT.LearningNodeNB
-
- getClassVotes(Instance, EFDT) - Method in class moa.classifiers.trees.EFDT.LearningNodeNBAdaptive
-
- getClassVotes(Instance, EFDT) - Method in class moa.classifiers.trees.EFDT.Node
-
- getClassVotes(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
-
- getClassVotes(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNB
-
- getClassVotes(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNBAdaptive
-
- getClassVotes(Instance, HoeffdingOptionTree) - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.ARFHoeffdingTree.LearningNodeNB
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.ARFHoeffdingTree.LearningNodeNBAdaptive
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTreeClassifLeaves.LearningNodeHATClassifier
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.LearningNodeNB
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.LearningNodeNBAdaptive
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTree.Node
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.HoeffdingTreeClassifLeaves.LearningNodeClassifier
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNB
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNBAdaptive
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNB
-
- getClassVotes(Instance, HoeffdingTree) - Method in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNBAdaptive
-
- getClassVotesFromLeaf(Instance) - Method in class moa.classifiers.trees.iadem.Iadem3
-
- getCLIChar() - Method in class com.github.javacliparser.AbstractOption
-
- getCLIChar() - Method in interface com.github.javacliparser.Option
-
Gets the Command Line Interface text of this option
- getCLICreationString(Class<?>) - Method in class moa.options.AbstractOptionHandler
-
- getCLICreationString(Class<?>) - Method in interface moa.options.OptionHandler
-
Gets the Command Line Interface text to create the object
- getCLIString() - Method in class moa.clusterers.meta.BooleanParameter
-
- getCLIString() - Method in class moa.clusterers.meta.CategoricalParameter
-
- getCLIString() - Method in class moa.clusterers.meta.IntegerParameter
-
- getCLIString() - Method in interface moa.clusterers.meta.IParameter
-
- getCLIString() - Method in class moa.clusterers.meta.NumericalParameter
-
- getCLIString() - Method in class moa.clusterers.meta.OrdinalParameter
-
- getCLIValueString() - Method in class moa.clusterers.meta.BooleanParameter
-
- getCLIValueString() - Method in class moa.clusterers.meta.CategoricalParameter
-
- getCLIValueString() - Method in class moa.clusterers.meta.IntegerParameter
-
- getCLIValueString() - Method in interface moa.clusterers.meta.IParameter
-
- getCLIValueString() - Method in class moa.clusterers.meta.NumericalParameter
-
- getCLIValueString() - Method in class moa.clusterers.meta.OrdinalParameter
-
- getClock() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getClusterClassWeight(int, int) - Method in class moa.evaluation.MembershipMatrix
-
- getClusterClassWeightByLabel(int, int) - Method in class moa.evaluation.MembershipMatrix
-
- getClusterer0() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- getClusterer0() - Method in class moa.gui.clustertab.ClusteringSetupTab
-
- getClusterer0() - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- getClusterer1() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- getClusterer1() - Method in class moa.gui.clustertab.ClusteringSetupTab
-
- getClusterer1() - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- getClusterID() - Method in class moa.gui.visualization.ClusterPanel
-
- getClusterID() - Method in class moa.gui.visualization.OutlierPanel
-
- getClustering() - Method in class moa.cluster.Clustering
-
- getClustering() - Method in interface moa.clusterers.macro.IDenseMacroCluster
-
- getClustering() - Method in class moa.clusterers.macro.NonConvexCluster
-
- getClustering(long, int) - Method in class moa.clusterers.clustree.ClusTree
-
- getClustering(Clustering) - Method in class moa.clusterers.macro.AbstractMacroClusterer
-
- getClustering(Clustering) - Method in class moa.clusterers.macro.dbscan.DBScan
-
- getClustering(Clustering) - Method in interface moa.clusterers.macro.IMacroClusterer
-
- getClusteringCopy() - Method in class moa.cluster.Clustering
-
- getClusteringFeature() - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Gets the ClusteringFeature of this node.
- getClusteringResult() - Method in interface moa.clusterers.Clusterer
-
- getClusteringResult() - Method in class moa.clusterers.ClusterGenerator
-
- getClusteringResult() - Method in class moa.clusterers.clustream.Clustream
-
- getClusteringResult() - Method in class moa.clusterers.clustream.WithKmeans
-
- getClusteringResult() - Method in class moa.clusterers.clustree.ClusTree
-
- getClusteringResult() - Method in class moa.clusterers.CobWeb
-
- getClusteringResult() - Method in class moa.clusterers.denstream.WithDBSCAN
-
- getClusteringResult() - Method in class moa.clusterers.dstream.Dstream
-
- getClusteringResult() - Method in class moa.clusterers.kmeanspm.BICO
-
- getClusteringResult() - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- getClusteringResult() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getClusteringResult() - Method in class moa.clusterers.streamkm.StreamKM
-
- getClusteringResult() - Method in class moa.clusterers.WekaClusteringAlgorithm
-
- getClusteringResult(Clustering) - Method in class moa.clusterers.clustream.WithKmeans
-
- getClusterLabel() - Method in class moa.clusterers.dstream.GridCluster
-
- getClusterLabel() - Method in class moa.gui.visualization.ClusterPanel
-
- getClusterLabel() - Method in class moa.gui.visualization.OutlierPanel
-
- getClusterSpecificInfo(ArrayList<String>, ArrayList<String>) - Method in class moa.cluster.Cluster
-
- getClusterSpecificInfo(ArrayList<String>, ArrayList<String>) - Method in class moa.cluster.SphereCluster
-
- getClusterSpecificInfo(ArrayList<String>, ArrayList<String>) - Method in class moa.clusterers.clustream.ClustreamKernel
-
- getClusterSum(int) - Method in class moa.evaluation.MembershipMatrix
-
- getColor() - Method in class moa.clusterers.macro.ColorObject
-
- getColor(int) - Static method in class moa.clusterers.macro.ColorArray
-
- getColorBox() - Method in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Returns the class selection combo box if the parent component wants to
place it in itself or in some component other than this component.
- getColorCoding() - Method in class moa.tasks.meta.MetaMainTask
-
Get the color coding for this task (the color which is used for multi-curve plots).
- getColoringIndex() - Method in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Get the coloring (class) index for the plot
- getColumnCount() - Method in class moa.gui.active.ALTaskManagerPanel.TaskTableModel
-
- getColumnCount() - Method in class moa.gui.AuxiliarTaskManagerPanel.TaskTableModel
-
- getColumnCount() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
-
- getColumnCount() - Method in class moa.gui.experimentertab.TaskManagerTabPanel.TaskTableModel
-
- getColumnCount() - Method in class moa.gui.LineGraphViewPanel.PlotTableModel
-
- getColumnCount() - Method in class moa.gui.MultiLabelTaskManagerPanel.TaskTableModel
-
- getColumnCount() - Method in class moa.gui.MultiTargetTaskManagerPanel.TaskTableModel
-
- getColumnCount() - Method in class moa.gui.PreviewTableModel
-
- getColumnCount() - Method in class moa.gui.RegressionTaskManagerPanel.TaskTableModel
-
- getColumnCount() - Method in class moa.gui.TaskManagerPanel.TaskTableModel
-
- getColumnName(int) - Method in class moa.gui.active.ALTaskManagerPanel.TaskTableModel
-
- getColumnName(int) - Method in class moa.gui.AuxiliarTaskManagerPanel.TaskTableModel
-
- getColumnName(int) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
-
- getColumnName(int) - Method in class moa.gui.experimentertab.TaskManagerTabPanel.TaskTableModel
-
- getColumnName(int) - Method in class moa.gui.LineGraphViewPanel.PlotTableModel
-
- getColumnName(int) - Method in class moa.gui.MultiLabelTaskManagerPanel.TaskTableModel
-
- getColumnName(int) - Method in class moa.gui.MultiTargetTaskManagerPanel.TaskTableModel
-
- getColumnName(int) - Method in class moa.gui.PreviewTableModel
-
- getColumnName(int) - Method in class moa.gui.RegressionTaskManagerPanel.TaskTableModel
-
- getColumnName(int) - Method in class moa.gui.TaskManagerPanel.TaskTableModel
-
- getConfidence() - Static method in class moa.classifiers.trees.iadem.IademCommonProcedures
-
- getConfidence(int) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- getConnectionValue(CMM_GTAnalysis.CMMPoint, int) - Method in class moa.evaluation.CMM_GTAnalysis
-
Calculate the connection of a point to a cluster
- getCoordinates() - Method in class moa.clusterers.dstream.DensityGrid
-
- getCopy() - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- getCopy() - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- getCopy() - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
Deprecated.
- getCopy() - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- getCoresetCentres() - Method in class moa.clusterers.streamkm.CoresetCostTriple
-
- getCoresetCost() - Method in class moa.clusterers.streamkm.CoresetCostTriple
-
- getCountBelow(double) - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- getCountNominalAttrib(ArrayList<Predicates>) - Method in class moa.classifiers.rules.RuleClassifier
-
- getCPUSecondsElapsed() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- getCPUSecondsElapsed() - Method in class moa.tasks.TaskThread
-
- getCreationTime() - Method in class moa.clusterers.denstream.MicroCluster
-
- getCumulativeSum() - Method in class moa.classifiers.rules.driftdetection.PageHinkleyTest
-
- getCurrent() - Method in class moa.classifiers.rules.featureranking.MeritFeatureRanking.RuleInformation
-
- getCurrentActivityDescription() - Method in class moa.tasks.NullMonitor
-
- getCurrentActivityDescription() - Method in class moa.tasks.StandardTaskMonitor
-
- getCurrentActivityDescription() - Method in interface moa.tasks.TaskMonitor
-
Gets the description of the current activity.
- getCurrentActivityFracComplete() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- getCurrentActivityFracComplete() - Method in class moa.tasks.TaskThread
-
- getCurrentActivityFractionComplete() - Method in class moa.tasks.NullMonitor
-
- getCurrentActivityFractionComplete() - Method in class moa.tasks.StandardTaskMonitor
-
- getCurrentActivityFractionComplete() - Method in interface moa.tasks.TaskMonitor
-
Gets the percentage done of the current activity
- getCurrentActivityString() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- getCurrentActivityString() - Method in class moa.tasks.TaskThread
-
- getCurrenTask() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- getCurrentError() - Method in class moa.classifiers.rules.core.Rule
-
- getCurrentError() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getCurrentError() - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- getCurrentError() - Method in class moa.classifiers.rules.errormeasurers.ErrorMeasurement
-
- getCurrentError() - Method in class moa.classifiers.rules.errormeasurers.MeanAbsoluteDeviation
-
- getCurrentError() - Method in class moa.classifiers.rules.errormeasurers.RootMeanSquaredError
-
- getCurrentError() - Method in class moa.classifiers.rules.functions.AdaptiveNodePredictor
-
- getCurrentError() - Method in interface moa.classifiers.rules.functions.AMRulesLearner
-
- getCurrentError() - Method in class moa.classifiers.rules.functions.LowPassFilteredLearner
-
- getCurrentError() - Method in class moa.classifiers.rules.functions.Perceptron
-
- getCurrentError() - Method in class moa.classifiers.rules.functions.TargetMean
-
- getCurrentError() - Method in class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiLabelErrorMeasurer
-
- getCurrentError() - Method in class moa.classifiers.rules.multilabel.errormeasurers.MeanAbsoluteDeviationMT
-
- getCurrentError() - Method in interface moa.classifiers.rules.multilabel.errormeasurers.MultiLabelErrorMeasurer
-
- getCurrentError() - Method in class moa.classifiers.rules.multilabel.errormeasurers.RelativeMeanAbsoluteDeviationMT
-
- getCurrentError() - Method in class moa.classifiers.rules.multilabel.errormeasurers.RelativeRootMeanSquaredErrorMT
-
- getCurrentError() - Method in class moa.classifiers.rules.multilabel.errormeasurers.RootMeanSquaredErrorMT
-
- getCurrentError(int) - Method in class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiLabelErrorMeasurer
-
- getCurrentError(int) - Method in class moa.classifiers.rules.multilabel.errormeasurers.MeanAbsoluteDeviationMT
-
- getCurrentError(int) - Method in interface moa.classifiers.rules.multilabel.errormeasurers.MultiLabelErrorMeasurer
-
- getCurrentError(int) - Method in class moa.classifiers.rules.multilabel.errormeasurers.RelativeMeanAbsoluteDeviationMT
-
- getCurrentError(int) - Method in class moa.classifiers.rules.multilabel.errormeasurers.RelativeRootMeanSquaredErrorMT
-
- getCurrentError(int) - Method in class moa.classifiers.rules.multilabel.errormeasurers.RootMeanSquaredErrorMT
-
- getCurrentErrors() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getCurrentErrors() - Method in class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiLabelErrorMeasurer
-
- getCurrentErrors() - Method in class moa.classifiers.rules.multilabel.errormeasurers.MeanAbsoluteDeviationMT
-
- getCurrentErrors() - Method in interface moa.classifiers.rules.multilabel.errormeasurers.MultiLabelErrorMeasurer
-
- getCurrentErrors() - Method in class moa.classifiers.rules.multilabel.errormeasurers.RelativeMeanAbsoluteDeviationMT
-
- getCurrentErrors() - Method in class moa.classifiers.rules.multilabel.errormeasurers.RelativeRootMeanSquaredErrorMT
-
- getCurrentErrors() - Method in class moa.classifiers.rules.multilabel.errormeasurers.RootMeanSquaredErrorMT
-
- getCurrentFeatureImportances() - Method in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- getCurrentStatusString() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- getCurrentStatusString() - Method in class moa.tasks.TaskThread
-
- getCurrentTimestamp() - Static method in class moa.gui.visualization.RunOutlierVisualizer
-
- getCurrentTimestamp() - Static method in class moa.gui.visualization.RunVisualizer
-
- getCurrGridDensity(int, double) - Method in class moa.clusterers.dstream.CharacteristicVector
-
- getCurrTime() - Method in class moa.clusterers.dstream.Dstream
-
- getCustomEditor() - Method in class weka.gui.MOAClassOptionEditor
-
Gets the custom editor component.
- getCut(int) - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- getCut(int) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- getCut(int) - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- getCut(int) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- getCutoff() - Method in class moa.clusterers.CobWeb
-
get the cutoff
- getData() - Method in class moa.clusterers.clustree.Entry
-
Getter for the data.
- getData() - Method in interface moa.core.Example
-
- getData() - Method in class moa.core.InstanceExample
-
- getData() - Method in class moa.evaluation.preview.Preview
-
- getData() - Method in class moa.recommender.data.MemRecommenderData
-
- getData() - Method in interface moa.recommender.data.RecommenderData
-
- getData() - Method in class moa.recommender.predictor.BaselinePredictor
-
- getData() - Method in class moa.recommender.predictor.BRISMFPredictor
-
- getData() - Method in interface moa.recommender.predictor.RatingPredictor
-
- getData() - Method in class moa.recommender.rc.predictor.impl.BaselinePredictor
-
- getData() - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- getData() - Method in interface moa.recommender.rc.predictor.RatingPredictor
-
- getDataObjectArray() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
Returns an array of all the DataObjects in the set.
- getDataset(int, int) - Method in class moa.clusterers.WekaClusteringAlgorithm
-
- getDataSetsPerClass() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
Separates the objects in this data set according to their class label
- getDecayFactor() - Method in class moa.clusterers.dstream.Dstream
-
- getDecayHorizon() - Method in class moa.streams.clustering.ClusteringStream
-
- getDecayThreshold() - Method in class moa.streams.clustering.ClusteringStream
-
- getDefaultCLIString() - Method in class com.github.javacliparser.AbstractClassOption
-
- getDefaultCLIString() - Method in class com.github.javacliparser.FlagOption
-
- getDefaultCLIString() - Method in class com.github.javacliparser.FloatOption
-
- getDefaultCLIString() - Method in class com.github.javacliparser.IntOption
-
- getDefaultCLIString() - Method in class com.github.javacliparser.ListOption
-
- getDefaultCLIString() - Method in class com.github.javacliparser.MultiChoiceOption
-
- getDefaultCLIString() - Method in interface com.github.javacliparser.Option
-
Gets the Command Line Interface text
- getDefaultCLIString() - Method in class com.github.javacliparser.StringOption
-
- getDefaultCLIString() - Method in class moa.options.AbstractClassOption
-
- getDefaultEnabled() - Method in class moa.evaluation.Accuracy
-
- getDefaultEnabled() - Method in class moa.evaluation.ChangeDetectionMeasures
-
- getDefaultEnabled() - Method in class moa.evaluation.CMM
-
- getDefaultEnabled() - Method in class moa.evaluation.EntropyCollection
-
- getDefaultEnabled() - Method in class moa.evaluation.MeasureCollection
-
- getDefaultEnabled() - Method in class moa.evaluation.OutlierPerformance
-
- getDefaultEnabled() - Method in class moa.evaluation.RegressionAccuracy
-
- getDefaultEnabled() - Method in class moa.evaluation.SilhouetteCoefficient
-
- getDefaultEnabled() - Method in class moa.evaluation.SSQ
-
- getDefaultEnabled() - Method in class moa.evaluation.StatisticalCollection
-
- getDefaultFileExtension() - Method in class com.github.javacliparser.FileOption
-
- getDefaultHeight() - Method in class moa.clusterers.clustree.ClusTree
-
- getDefaultOptionIndex() - Method in class com.github.javacliparser.MultiChoiceOption
-
- getDefaultSplitMeasure() - Static method in class moa.classifiers.trees.iadem.IademSplitCriterion
-
- getDefaultTabs() - Static method in class moa.gui.GUIDefaults
-
returns an array with the classnames of all default tabs to
display as tabs in the GUI.
- getDelay() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Gets the length of the delay in the change detected.
- getDelay() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector
-
Gets the length of the delay in the change detected.
- getDenormalizedOutput(double[]) - Method in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- getDensityTimeStamp() - Method in class moa.clusterers.dstream.CharacteristicVector
-
- getDescription() - Method in class moa.gui.AbstractTabPanel
-
Returns a short description (can be used as tool tip) of the tab, or contributor, etc.
- getDescription() - Method in class moa.gui.ALTabPanel
-
- getDescription() - Method in class moa.gui.AuxiliarTabPanel
-
- getDescription() - Method in class moa.gui.ClassificationTabPanel
-
- getDescription() - Method in class moa.gui.clustertab.ClusteringTabPanel
-
- getDescription() - Method in class moa.gui.ConceptDriftTabPanel
-
- getDescription() - Method in class moa.gui.experimentertab.ExperimenterTabPanel
-
- getDescription() - Method in class moa.gui.featureanalysis.FeatureAnalysisTabPanel
-
- getDescription() - Method in class moa.gui.FileExtensionFilter
-
- getDescription() - Method in class moa.gui.MultiLabelTabPanel
-
- getDescription() - Method in class moa.gui.MultiTargetTabPanel
-
- getDescription() - Method in class moa.gui.outliertab.OutlierTabPanel
-
- getDescription() - Method in class moa.gui.RegressionTabPanel
-
- getDescription() - Method in class moa.gui.ScriptingTabPanel
-
Returns a short description (can be used as tool tip) of the tab, or contributor, etc.
- getDescription(StringBuilder, int) - Method in class com.github.javacliparser.Options
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.AbstractClassifier
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.active.budget.FixedBM
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.AttributeSplitSuggestion
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Returns a string representation of the model.
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.ADWINChangeDetector
-
- getDescription(StringBuilder, int) - Method in interface moa.classifiers.core.driftdetection.ChangeDetector
-
Returns a string representation of the model.
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.CusumDM
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.DDM
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.EDDM
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.EWMAChartDM
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.PageHinkleyDM
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.RDDM
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector.SeqDrift1
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.SeqDrift2
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.driftdetection.STEPD
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.statisticaltests.Cramer
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.core.statisticaltests.KNN
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.multilabel.core.splitcriteria.ICVarianceReduction
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.anomalydetection.AnomalinessRatioScore
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.anomalydetection.NoAnomalyDetection
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.anomalydetection.OddsRatioScore
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.CantellisInequality
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.ChebyshevInequality
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.GaussInequality
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.changedetection.NoChangeDetection
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.conditionaltests.NominalAttributeBinaryRulePredicate
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.NominalRulePredicate
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.NumericRulePredicate
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.Rule
-
MOA GUI output
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.splitcriteria.VarianceRatioSplitCriterion
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.voting.ExpNegErrorWeightedVote
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.voting.InverseErrorWeightedVote
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.voting.MinErrorWeightedVote
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.voting.OneMinusErrorWeightedVote
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.core.voting.UniformWeightedVote
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.errormeasurers.ErrorMeasurement
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.featureranking.AbstractFeatureRanking
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelNominalAttributeObserver
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.core.AttributeExpansionSuggestion
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.core.Literal
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultilabelInformationGain
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultiTargetVarianceRatio
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiLabelErrorMeasurer
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.inputselectors.MeritThreshold
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.inputselectors.SelectAllInputs
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.instancetransformers.InstanceAttributesSelector
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.instancetransformers.InstanceOutputAttributesSelector
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.instancetransformers.NoInstanceTransformation
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.outputselectors.EntropyThreshold
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.outputselectors.SelectAllOutputs
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.outputselectors.StdDevThreshold
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.outputselectors.VarianceThreshold
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.Predicates
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.rules.RuleClassification
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.EFDT.Node
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD.Node
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingTree.Node
-
- getDescription(StringBuilder, int) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- getDescription(StringBuilder, int) - Method in class moa.cluster.Cluster
-
- getDescription(StringBuilder, int) - Method in class moa.cluster.Clustering
-
- getDescription(StringBuilder, int) - Method in class moa.clusterers.AbstractClusterer
-
- getDescription(StringBuilder, int) - Method in class moa.clusterers.denstream.Timestamp
-
- getDescription(StringBuilder, int) - Method in class moa.clusterers.dstream.GridCluster
-
- getDescription(StringBuilder, int) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
- getDescription(StringBuilder, int) - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
- getDescription(StringBuilder, int) - Method in class moa.core.AutoExpandVector
-
- getDescription(StringBuilder, int) - Method in class moa.core.DoubleVector
-
- getDescription(StringBuilder, int) - Method in class moa.core.GaussianEstimator
-
- getDescription(StringBuilder, int) - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- getDescription(StringBuilder, int) - Method in class moa.core.Measurement
-
- getDescription(StringBuilder, int) - Method in class moa.core.utils.Converter
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicMultiLabelPerformanceEvaluator
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.LearningEvaluation
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.MeasureCollection
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.preview.LearningCurve
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.preview.PreviewCollection
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.preview.PreviewCollectionLearningCurveWrapper
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator
-
- getDescription(StringBuilder, int) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- getDescription(StringBuilder, int) - Method in interface moa.MOAObject
-
Returns a string representation of this object.
- getDescription(StringBuilder, int) - Method in class moa.recommender.data.MemRecommenderData
-
- getDescription(StringBuilder, int) - Method in class moa.recommender.dataset.impl.FlixsterDataset
-
- getDescription(StringBuilder, int) - Method in class moa.recommender.dataset.impl.JesterDataset
-
- getDescription(StringBuilder, int) - Method in class moa.recommender.dataset.impl.MovielensDataset
-
- getDescription(StringBuilder, int) - Method in class moa.recommender.predictor.BaselinePredictor
-
- getDescription(StringBuilder, int) - Method in class moa.recommender.predictor.BRISMFPredictor
-
- getDescription(StringBuilder, int) - Method in class moa.streams.ArffFileStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.BootstrappedStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.CachedInstancesStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.clustering.FileStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
TOOLS
- getDescription(StringBuilder, int) - Method in class moa.streams.clustering.SimpleCSVStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.ConceptDriftRealStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.ConceptDriftStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.FilteredStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.filters.AddNoiseFilter
-
- getDescription(StringBuilder, int) - Method in class moa.streams.filters.RBFFilter
-
- getDescription(StringBuilder, int) - Method in class moa.streams.filters.ReLUFilter
-
- getDescription(StringBuilder, int) - Method in class moa.streams.filters.RemoveDiscreteAttributeFilter
-
- getDescription(StringBuilder, int) - Method in class moa.streams.filters.ReplacingMissingValuesFilter
-
- getDescription(StringBuilder, int) - Method in class moa.streams.filters.SelectAttributesFilter
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.AgrawalGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.AssetNegotiationGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.HyperplaneGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.LEDGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.LEDGeneratorDrift
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.MixedGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.RandomRBFGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.RandomRBFGeneratorDrift
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.RandomTreeGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.SEAGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.SineGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.STAGGERGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.TextGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.WaveformGenerator
-
- getDescription(StringBuilder, int) - Method in class moa.streams.generators.WaveformGeneratorDrift
-
- getDescription(StringBuilder, int) - Method in class moa.streams.ImbalancedStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.IrrelevantFeatureAppenderStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.MultiFilteredStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.MultiLabelFilteredStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.MultiTargetArffFileStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.PartitioningStream
-
- getDescription(StringBuilder, int) - Method in class moa.streams.RecurrentConceptDriftStream
-
- getDescription(StringBuilder, int) - Method in class moa.tasks.AbstractTask
-
- getDescription(StringBuilder, int) - Method in class moa.tasks.FailedTaskReport
-
- getDescription(StringBuilder, int, InstanceInformation) - Method in class moa.classifiers.rules.core.conditionaltests.NominalAttributeBinaryRulePredicate
-
- getDescription(StringBuilder, int, InstanceInformation) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- getDescription(StringBuilder, int, InstanceInformation) - Method in class moa.classifiers.rules.core.NominalRulePredicate
-
- getDescription(StringBuilder, int, InstanceInformation) - Method in class moa.classifiers.rules.core.NumericRulePredicate
-
- getDescription(StringBuilder, int, InstanceInformation) - Method in interface moa.classifiers.rules.core.Predicate
-
- getDescription(StringBuilder, int, InstanceInformation) - Method in class moa.classifiers.rules.multilabel.core.Literal
-
- getDescriptions() - Static method in enum moa.tasks.Plot.LegendLocation
-
Gets an array of string descriptions - one for each enum value.
- getDescriptions() - Static method in enum moa.tasks.Plot.LegendType
-
Gets an array of string descriptions - one for each enum value.
- getDescriptions() - Static method in enum moa.tasks.Plot.PlotStyle
-
Gets an array of string descriptions = one for each enum value.
- getDescriptions() - Static method in enum moa.tasks.Plot.Terminal
-
Gets an array of string descriptions - one for each enum value.
- getDetect() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getDimensions() - Method in class moa.clusterers.dstream.DensityGrid
-
- getDisplayName() - Method in class moa.tasks.meta.MetaMainTask
-
Get the task's display name consisting of the general task name,
indentation showing the tree structure depending on the subtask level
and optionally a name suffix given from a supertask.
- getDistance(DataPoint) - Method in class moa.gui.visualization.DataPoint
-
- getDistanceFunction() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
returns the distance function currently in use.
- getDistanceFunction() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
returns the distance function currently in use.
- getDistances() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns the distances to the kNearest or 1 nearest neighbour currently
found with either the kNearestNeighbours or the nearestNeighbour method.
- getDistances() - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch
-
Returns the distances of the k nearest neighbours.
- getDistances() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Returns the distances of the k nearest neighbours.
- getDistanceVector(Instance) - Method in class moa.cluster.SphereCluster
-
- getDistanceVector(SphereCluster) - Method in class moa.cluster.SphereCluster
-
- getDL() - Method in class moa.clusterers.dstream.Dstream
-
- getDM() - Method in class moa.clusterers.dstream.Dstream
-
- getDontNormalize() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Gets whether if the attribute values are to be normazlied in distance
calculation.
- getEditComponent(Option) - Static method in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- getEditComponent(Option) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- getEditComponent(Option) - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- getEditComponent(Option) - Method in class weka.gui.MOAClassOptionEditor
-
- getEditedOption() - Method in class com.github.javacliparser.gui.ClassOptionEditComponent
-
- getEditedOption() - Method in class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
- getEditedOption() - Method in class com.github.javacliparser.gui.FileOptionEditComponent
-
- getEditedOption() - Method in class com.github.javacliparser.gui.FlagOptionEditComponent
-
- getEditedOption() - Method in class com.github.javacliparser.gui.FloatOptionEditComponent
-
- getEditedOption() - Method in class com.github.javacliparser.gui.IntOptionEditComponent
-
- getEditedOption() - Method in class com.github.javacliparser.gui.MultiChoiceOptionEditComponent
-
- getEditedOption() - Method in interface com.github.javacliparser.gui.OptionEditComponent
-
Gets the option of this component
- getEditedOption() - Method in class com.github.javacliparser.gui.StringOptionEditComponent
-
- getEditedOption() - Method in class moa.gui.WEKAClassOptionEditComponent
-
- getEMClusteringVariances(double[][], int) - Method in class moa.clusterers.outliers.AnyOut.util.EMProjectedClustering
-
Performs an EM clustering on the provided data set
!! Only the variances are calculated and used for point assignments !
!!! the number k' of returned clusters might be smaller than k !!!
- getEMClusteringVariancesBestChoice(double[][], int, int) - Method in class moa.clusterers.outliers.AnyOut.util.EMProjectedClustering
-
- getEnd() - Method in class com.yahoo.labs.samoa.instances.Range
-
- getEnd(int) - Method in class moa.streams.filters.Selection
-
- getEnsembleMemberWeight(int) - Method in class moa.classifiers.meta.ADOB
-
- getEnsembleMemberWeight(int) - Method in class moa.classifiers.meta.BOLE
-
- getEnsembleMemberWeight(int) - Method in class moa.classifiers.meta.OCBoost
-
- getEnsembleMemberWeight(int) - Method in class moa.classifiers.meta.OnlineSmoothBoost
-
- getEnsembleMemberWeight(int) - Method in class moa.classifiers.meta.OzaBoost
-
- getEnsembleMemberWeight(int) - Method in class moa.classifiers.meta.OzaBoostAdwin
-
- getEnsembleSize() - Method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- getEntries() - Method in class moa.clusterers.clustree.Node
-
Return an array with references to the children of this node.
- getEntryData(int) - Method in class moa.evaluation.preview.LearningCurve
-
- getEntryData(int) - Method in class moa.evaluation.preview.Preview
-
- getEntryData(int) - Method in class moa.evaluation.preview.PreviewCollection
-
- getEntryData(int) - Method in class moa.evaluation.preview.PreviewCollectionLearningCurveWrapper
-
- getEntryMeasurementCount(int) - Method in class moa.evaluation.preview.LearningCurve
-
- getEpsilon() - Method in class moa.classifiers.functions.AdaGrad
-
Get the epsilon value.
- getEpsilonPrime() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- getError() - Method in class moa.classifiers.rules.core.voting.Vote
-
- getError() - Method in class moa.classifiers.rules.multilabel.core.voting.MultiLabelVote
-
- getErrorEstimation() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- getErrorEstimation() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- getErrorEstimation() - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
-
- getErrorEstimation() - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- getErrors() - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getErrorWidth() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- getErrorWidth() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- getErrorWidth() - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
-
- getEstimador() - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- getEstimation() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Gets the prediction of next values.
- getEstimation() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getEstimation() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector
-
Gets the prediction of next values.
- getEstimation() - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- getEstimation() - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector.SeqDrift1
-
- getEstimation() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.SeqDrift2
-
Gets the prediction of next values.
- getEstimatorCopy() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- getEstimatorCopy() - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- getEstimatorInfo() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getEvalPanel() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- getEvalPanel() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- getEvaluationFrequency() - Method in class moa.streams.clustering.ClusteringStream
-
- getEvaluationMeasurements(Measurement[], LearningPerformanceEvaluator[]) - Method in class moa.tasks.EvaluatePrequentialCV
-
- getEvaluationMeasurements(Measurement[], LearningPerformanceEvaluator[]) - Method in class moa.tasks.EvaluatePrequentialDelayedCV
-
- getEventsList() - Method in class moa.gui.experimentertab.tasks.ConceptDriftMainTask
-
- getEventsList() - Method in class moa.streams.ArffFileStream
-
- getEventsList() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- getEventsList() - Method in interface moa.streams.generators.cd.ConceptDriftGenerator
-
- getEventsList() - Method in class moa.tasks.AuxiliarMainTask
-
- getEventsList() - Method in class moa.tasks.ClassificationMainTask
-
- getEventsList() - Method in class moa.tasks.ConceptDriftMainTask
-
- getEventsList() - Method in class moa.tasks.MultiLabelMainTask
-
- getEventsList() - Method in class moa.tasks.MultiTargetMainTask
-
- getEventsList() - Method in class moa.tasks.RegressionMainTask
-
- getEventType(int) - Method in class moa.evaluation.MeasureCollection
-
- getExpandedLearningLiteral() - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getF1Statistic() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getF1Statistic(int) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getFailureReason() - Method in class moa.tasks.FailedTaskReport
-
- getFastSplitSuggestion(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getFeatureImportances(boolean) - Method in interface moa.learners.featureanalysis.FeatureImportanceClassifier
-
Obtain the current importance for each feature.
- getFeatureImportances(boolean) - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTree
-
- getFeatureImportances(boolean) - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTreeEnsemble
-
- getFeatureRangeEndIndex() - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- getFeatureRangeStartIndex() - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- getFeatureRankings() - Method in class moa.classifiers.rules.featureranking.AbstractFeatureRanking
-
- getFeatureRankings() - Method in class moa.classifiers.rules.featureranking.BasicFeatureRanking
-
- getFeatureRankings() - Method in interface moa.classifiers.rules.featureranking.FeatureRanking
-
- getFeatureRankings() - Method in class moa.classifiers.rules.featureranking.MeritFeatureRanking
-
- getFeatureRankings() - Method in class moa.classifiers.rules.featureranking.NoFeatureRanking
-
- getFeatureRankings() - Method in class moa.classifiers.rules.featureranking.WeightedMajorityFeatureRanking
-
- getFeatures() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
-
Returns the features (label attribute excluded).
- getFeaturesAsArray() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
Returns an array with all the features of all the objects in the set.
- getFFRatio(int) - Method in class moa.classifiers.trees.ORTO.OptionNode
-
- getFile() - Method in class com.github.javacliparser.FileOption
-
- getFileChooserHeight() - Static method in class moa.gui.GUIDefaults
-
Returns the height for the file chooser.
- getFileChooserWidth() - Static method in class moa.gui.GUIDefaults
-
Returns the width for the file chooser.
- getFileName() - Method in class moa.gui.experimentertab.Measure
-
- getFinalResult() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- getFinalResult() - Method in class moa.tasks.TaskThread
-
- getFirst() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
returns the first element in the list.
- getFirst() - Method in class moa.recommender.rc.utils.Pair
-
- getFirstBlockTotal() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- getFlag(char, String[]) - Static method in class moa.core.Utils
-
Checks if the given array contains the flag "-Char".
- getFlag(String, String[]) - Static method in class moa.core.Utils
-
Checks if the given array contains the flag "-String".
- getFractionCorrectlyClassified() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getFractionIncorrectlyClassified() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getFrameHeight() - Static method in class moa.gui.GUIDefaults
-
Returns the height for the frame.
- getFrameWidth() - Static method in class moa.gui.GUIDefaults
-
Returns the width for the frame.
- getFriedmanPValue() - Method in class moa.gui.experimentertab.statisticaltests.StatisticalTest
-
Return the p-value computed by Friedman test.
- getGeneratingClusters() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- getGenerator() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Returns the current MOA stream generator in use.
- getGlobalMean() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getGlobalMean() - Method in interface moa.recommender.rc.data.RecommenderData
-
- getGMean() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- getGMean() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- getGraphCanvas() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- getGraphCanvas() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- getGridDensity() - Method in class moa.clusterers.dstream.CharacteristicVector
-
- getGrids() - Method in class moa.clusterers.dstream.GridCluster
-
- getGroundTruth() - Method in class moa.cluster.Cluster
-
- getGT0Cluster(int) - Method in class moa.evaluation.CMM_GTAnalysis
-
Return cluster
- getHalf(boolean) - Method in class moa.classifiers.meta.DACC
-
Returns the best (or worst) half of classifiers in the adaptive ensemble.
- getHead() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- getHeader() - Method in class moa.streams.ArffFileStream
-
- getHeader() - Method in class moa.streams.BootstrappedStream
-
- getHeader() - Method in class moa.streams.CachedInstancesStream
-
- getHeader() - Method in class moa.streams.clustering.FileStream
-
- getHeader() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- getHeader() - Method in class moa.streams.clustering.SimpleCSVStream
-
- getHeader() - Method in class moa.streams.ConceptDriftRealStream
-
- getHeader() - Method in class moa.streams.ConceptDriftStream
-
- getHeader() - Method in interface moa.streams.ExampleStream
-
Gets the header of this stream.
- getHeader() - Method in class moa.streams.FilteredStream
-
- getHeader() - Method in class moa.streams.filters.AddNoiseFilter
-
- getHeader() - Method in class moa.streams.filters.RBFFilter
-
- getHeader() - Method in class moa.streams.filters.ReLUFilter
-
- getHeader() - Method in class moa.streams.filters.RemoveDiscreteAttributeFilter
-
- getHeader() - Method in class moa.streams.filters.ReplacingMissingValuesFilter
-
- getHeader() - Method in class moa.streams.filters.SelectAttributesFilter
-
- getHeader() - Method in class moa.streams.generators.AgrawalGenerator
-
- getHeader() - Method in class moa.streams.generators.AssetNegotiationGenerator
-
- getHeader() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- getHeader() - Method in class moa.streams.generators.HyperplaneGenerator
-
- getHeader() - Method in class moa.streams.generators.LEDGenerator
-
- getHeader() - Method in class moa.streams.generators.MixedGenerator
-
- getHeader() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- getHeader() - Method in class moa.streams.generators.multilabel.MultilabelArffFileStream
-
- getHeader() - Method in class moa.streams.generators.RandomRBFGenerator
-
- getHeader() - Method in class moa.streams.generators.RandomTreeGenerator
-
- getHeader() - Method in class moa.streams.generators.SEAGenerator
-
- getHeader() - Method in class moa.streams.generators.SineGenerator
-
- getHeader() - Method in class moa.streams.generators.STAGGERGenerator
-
- getHeader() - Method in class moa.streams.generators.TextGenerator
-
- getHeader() - Method in class moa.streams.generators.WaveformGenerator
-
- getHeader() - Method in class moa.streams.ImbalancedStream
-
- getHeader() - Method in class moa.streams.IrrelevantFeatureAppenderStream
-
- getHeader() - Method in class moa.streams.MultiFilteredStream
-
- getHeader() - Method in class moa.streams.MultiLabelFilteredStream
-
- getHeader() - Method in class moa.streams.MultiTargetArffFileStream
-
- getHeader() - Method in class moa.streams.PartitioningStream
-
- getHeadOptionCount() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- getHeight() - Method in class moa.clusterers.clustree.ClusTree
-
Return the current height of the tree.
- getHeight() - Method in class moa.gui.experimentertab.ImageChart
-
Return the height.
- getHelp(StringBuilder, int) - Method in class com.github.javacliparser.Options
-
- getHelpString() - Method in class com.github.javacliparser.Options
-
- getHelpText() - Method in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- getHeuristicMeasureLower(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- getHeuristicMeasureUpper(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- getHighlightedClusterPanel() - Method in class moa.gui.visualization.StreamPanel
-
- getHighlightedOutlierPanel() - Method in class moa.gui.visualization.StreamOutlierPanel
-
- getHoldoutAUC() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- getHullDistance(SphereCluster) - Method in class moa.cluster.SphereCluster
-
- getIADEM_HoeffdingBound(double, double) - Static method in class moa.classifiers.trees.iadem.IademCommonProcedures
-
- getId() - Method in class moa.cluster.Cluster
-
- getId() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
-
Returns the id for the DataObject.
- getIdxs() - Method in class moa.recommender.rc.utils.DenseVector
-
- getIdxs() - Method in class moa.recommender.rc.utils.SparseVector
-
- getIdxs() - Method in class moa.recommender.rc.utils.Vector
-
- getImanPValue() - Method in class moa.gui.experimentertab.statisticaltests.StatisticalTest
-
Return the p-value Iman and Daveport test.
- getInclusionProbability(Instance) - Method in class moa.cluster.CFCluster
-
- getInclusionProbability(Instance) - Method in class moa.cluster.Cluster
-
Returns the probability of the given point belonging to
this cluster.
- getInclusionProbability(Instance) - Method in class moa.cluster.SphereCluster
-
- getInclusionProbability(Instance) - Method in class moa.clusterers.clustream.ClustreamKernel
-
See interface Cluster
- getInclusionProbability(Instance) - Method in class moa.clusterers.clustree.ClusKernel
-
- getInclusionProbability(Instance) - Method in class moa.clusterers.denstream.MicroCluster
-
- getInclusionProbability(Instance) - Method in class moa.clusterers.dstream.DensityGrid
-
Provides the probability of the argument instance belonging to the density grid in question.
- getInclusionProbability(Instance) - Method in class moa.clusterers.dstream.GridCluster
-
Iterates through the DensityGrids in the cluster and calculates the inclusion probability for each.
- getInclusionProbability(Instance) - Method in class moa.clusterers.macro.NonConvexCluster
-
- getInclusionProbability(CMM_GTAnalysis.CMMPoint) - Method in class moa.evaluation.CMM_GTAnalysis.GTCluster
-
Calculate the probability of the point being covered through the cluster
- getIndex() - Method in class moa.gui.experimentertab.Measure
-
Returns the index of measure
- getIndex(ArrayList<PValuePerTwoAlgorithm>, String, String) - Static method in class moa.gui.experimentertab.statisticaltests.PValuePerTwoAlgorithm
-
- getIndexCorrespondence(int[], int[]) - Static method in class moa.classifiers.rules.core.Utils
-
- getIndexName() - Method in class moa.evaluation.preview.PreviewCollection
-
- getIndexValues() - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Gets the index values.
- getIndicesIrrelevants() - Method in class com.yahoo.labs.samoa.instances.Instances
-
Returns the indices of the irrelevant features indicesIrrelevants.
- getIndicesRelevants() - Method in class com.yahoo.labs.samoa.instances.Instances
-
Returns the indices of the relevant features indicesRelevants.
- getInfo() - Method in class moa.cluster.Cluster
-
- getInfo() - Method in class moa.gui.visualization.OutlierPanel
-
- getInfo(int, int) - Method in class moa.gui.visualization.DataPoint
-
- getInfogainSum() - Method in class moa.classifiers.trees.EFDT.Node
-
- getInitalBuildTimestamp() - Method in class moa.evaluation.MembershipMatrix
-
- getInitialDirectory() - Static method in class moa.gui.GUIDefaults
-
Returns the initial directory for the file chooser used for opening
datasets.
- getInputAttributeNameString(InstancesHeader, int) - Static method in class com.yahoo.labs.samoa.instances.InstancesHeader
-
- getInputsCovered() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getInputsToLearn() - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getInputString() - Method in class moa.tasks.ipynb.OptionsString
-
- getInputValues() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- getInstance() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
-
Return the Instance of the DataObject.
- getInstance() - Static method in class moa.gui.featureanalysis.FeatureImportancePanel
-
Singleton design pattern
- getInstanceInformation() - Method in class com.yahoo.labs.samoa.instances.InstancesHeader
-
- getInstances() - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction
-
returns the instances currently set.
- getInstances() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
returns the instances currently set.
- getInstances() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
returns the instances currently set.
- getInstances() - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Gets the working set of instances.
- getInstancesSeen() - Method in class moa.classifiers.rules.core.Rule
-
- getInstancesSeen() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getInstancesSeen() - Method in class moa.classifiers.rules.functions.Perceptron
-
- getInstanceValues(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getInstNodeCountSinceVirtual() - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getInstSeenSinceLastSplitAttempt() - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getIntEndIndex() - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- GetInterval() - Method in interface moa.clusterers.outliers.MyBaseOutlierDetector.ProgressInfo
-
- getIntStartIndex() - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- getInvertSelection() - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction
-
Gets whether the matching sense of attribute indices is inverted or not.
- getInvertSelection() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Gets whether the matching sense of attribute indices is inverted or not.
- getIrrelevantEntry(double) - Method in class moa.clusterers.clustree.Node
-
If there exists an entry, whose relevance is under the threshold given
as a parameter to the tree, this entry is returned.
- getItemCount() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- getItemFeatures(int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- getItems() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getItems() - Method in interface moa.recommender.rc.data.RecommenderData
-
- getKappa() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- getKappa() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- getKappaStatistic() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getKappaTemporalStatistic() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getKthNearest() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap
-
returns the kth nearest element or null if none there.
- getL() - Method in class moa.core.utils.Converter
-
- getLabel() - Method in class moa.clusterers.dstream.CharacteristicVector
-
- getLabel() - Method in class moa.evaluation.CMM_GTAnalysis.GTCluster
-
The original class label the cluster represents
- getLambda() - Method in class moa.classifiers.functions.SGD
-
Get the current value of lambda
- getLambda() - Method in class moa.classifiers.functions.SGDMultiClass
-
Get the current value of lambda
- getLambda() - Method in class moa.classifiers.functions.SPegasos
-
Get the current value of lambda
- getLast() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
returns the last element in the list.
- getLastCell() - Method in class moa.tasks.ipynb.NotebookBuilder
-
- getLastEditTimestamp() - Method in class moa.clusterers.denstream.MicroCluster
-
- getLastLabelAcqReport() - Method in interface moa.classifiers.active.ALClassifier
-
Returns true if the previously chosen instance was added to the training set
of the active learner.
- getLastLabelAcqReport() - Method in class moa.classifiers.active.ALRandom
-
- getLastLabelAcqReport() - Method in class moa.classifiers.active.ALUncertainty
-
- getLastLabelAcqReport() - Method in interface moa.classifiers.active.budget.BudgetManager
-
Returns the number of labels that have been chosen for acquisition since
the last report.
- getLastLabelAcqReport() - Method in class moa.classifiers.active.budget.FixedBM
-
- getLastValue(int) - Method in class moa.evaluation.MeasureCollection
-
- getLatestPreviewGrabTimeSeconds() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- getLatestPreviewGrabTimeSeconds() - Method in class moa.tasks.TaskThread
-
- getLatestResultPreview() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- getLatestResultPreview() - Method in class moa.tasks.NullMonitor
-
- getLatestResultPreview() - Method in class moa.tasks.StandardTaskMonitor
-
- getLatestResultPreview() - Method in interface moa.tasks.TaskMonitor
-
Gets the current result to preview
- getLatestResultPreview() - Method in class moa.tasks.TaskThread
-
- getLearnerToUse(Instance, int) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getLearnerToUse(Instance, int) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- getLearningAttributes() - Method in class moa.classifiers.rules.featureranking.messages.MeritCheckMessage
-
- getLearningCurve() - Method in class moa.evaluation.preview.PreviewCollectionLearningCurveWrapper
-
- getLearningNode() - Method in class moa.classifiers.rules.core.Rule
-
getLearningNode Method This is the way to pass info for other classes.
- getLearningNode() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getLearningRate() - Method in class moa.classifiers.functions.SGD
-
Get the learning rate.
- getLearningRate() - Method in class moa.classifiers.functions.SGDMultiClass
-
Get the learning rate.
- getLeaves() - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getLeaves() - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- getLeaves() - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- getLeaves() - Method in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- getLeftClassDist(double) - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- getLeftClassDist(double) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- getLeftClassDist(double) - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- getLeftClassDist(double) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- getLeftStreamPanel() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- getLeftStreamPanel() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- getLevel() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- getLevel() - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- getLevel() - Method in class moa.classifiers.trees.FIMTDD.Node
-
- getLevel(ClusTree) - Method in class moa.clusterers.clustree.Node
-
Returns the level at which this node is in the tree.
- getList() - Method in class com.github.javacliparser.ListOption
-
- getLiterals() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getLogPanel() - Method in class moa.gui.clustertab.ClusteringSetupTab
-
- getLogPanel() - Method in class moa.gui.outliertab.OutlierSetupTab
-
- getLossFunction() - Method in class moa.classifiers.functions.SGD
-
Get the current loss function.
- getLossFunction() - Method in class moa.classifiers.functions.SGDMultiClass
-
Get the current loss function.
- getLossFunction() - Method in class moa.classifiers.functions.SPegasos
-
Get the current loss function.
- getLowerQuartile(int) - Method in class moa.evaluation.MeasureCollection
-
- getMainTree() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- getMainTree() - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- getMajorityClassVotes(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getMaxAltSubtreesPerNode() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- getMaxAttValsObserved() - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
-
- getMaxInclusionProbability(Instance) - Method in class moa.cluster.Clustering
-
- getMAXIndexes() - Method in class moa.classifiers.meta.DACC
-
Returns the classifiers that vote for the final prediction
when the MAX combination function is selected
- getMaxInstInLeaf() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Get the maximum number of instances in a leaf.
- getMaxNestingLevels() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- getMaxNumberOfBins() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getMaxOfValues() - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- getMaxOfValues() - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- getMaxOfValues() - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- getMaxOfValues() - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- getMaxRating() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getMaxRating() - Method in interface moa.recommender.rc.data.RecommenderData
-
- getMaxRelativeNodeWidth(double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns the maximum attribute width of instances/points
in a KDTreeNode relative to the whole dataset.
- getMaxSize() - Method in class moa.core.FixedLengthList
-
- getMaxTabUndo() - Static method in class moa.gui.GUIDefaults
-
Returns the maximum of undos for closing pages/tabs.
- getMaxValue() - Method in class com.github.javacliparser.FloatOption
-
- getMaxValue() - Method in class com.github.javacliparser.IntOption
-
- getMaxValue(int) - Method in class moa.evaluation.MeasureCollection
-
- getMaxXValue() - Method in class moa.gui.visualization.AbstractGraphCanvas
-
Returns the maximum value for the x-axis.
- getMaxXValue() - Method in class moa.gui.visualization.ParamGraphCanvas
-
- getMaxXValue() - Method in class moa.gui.visualization.ProcessGraphCanvas
-
- getMean() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- getMean() - Method in class moa.core.GaussianEstimator
-
- getMean(int) - Method in class moa.evaluation.MeasureCollection
-
- getMeanError() - Method in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- getMeanError() - Method in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- getMeanError() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- getMeanError() - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- getMeanError() - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- getMeanError() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- getMeanPreviews() - Method in class moa.evaluation.preview.MeanPreviewCollection
-
- getMeanRunningTime() - Method in class moa.evaluation.MeasureCollection
-
- getMeasure() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getMeasure(String) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns the value of the named measure.
- getMeasureCollection() - Method in enum moa.gui.experimentertab.ExpPreviewPanel.TypePanel
-
- getMeasureCollection() - Method in enum moa.gui.PreviewPanel.TypePanel
-
- getMeasurement(int, int) - Method in class moa.evaluation.preview.LearningCurve
-
- getMeasurementName(int) - Method in class moa.evaluation.preview.LearningCurve
-
- getMeasurementName(int) - Method in class moa.evaluation.preview.Preview
-
- getMeasurementName(int) - Method in class moa.evaluation.preview.PreviewCollection
-
- getMeasurementName(int) - Method in class moa.evaluation.preview.PreviewCollectionLearningCurveWrapper
-
- getMeasurementNameCount() - Method in class moa.evaluation.preview.LearningCurve
-
- getMeasurementNameCount() - Method in class moa.evaluation.preview.Preview
-
- getMeasurementNameCount() - Method in class moa.evaluation.preview.PreviewCollection
-
- getMeasurementNameCount() - Method in class moa.evaluation.preview.PreviewCollectionLearningCurveWrapper
-
- getMeasurementNamed(String, Measurement[]) - Static method in class moa.core.Measurement
-
- getMeasurementNames() - Method in class moa.evaluation.preview.Preview
-
- getMeasurements() - Method in class moa.evaluation.LearningEvaluation
-
- getMeasurementsDescription(Measurement[], StringBuilder, int) - Static method in class moa.core.Measurement
-
- getMeasurePerformance() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Gets whether performance statistics are being calculated or not.
- getMeasures() - Method in class moa.gui.clustertab.ClusteringSetupTab
-
- getMeasures() - Method in class moa.gui.experimentertab.ReadFile
-
Returns the common measures to all algorithms.
- getMeasures() - Method in class moa.gui.outliertab.OutlierSetupTab
-
- getMeasureSelected() - Method in class moa.gui.visualization.GraphCanvas
-
- getMeasuresPerData(List<Stream>) - Method in class moa.gui.experimentertab.Algorithm
-
Returns a list of measures per dataset.
- getMeasureValue(String) - Method in class moa.cluster.Cluster
-
- getMeasureValue(String) - Method in class moa.gui.visualization.DataPoint
-
- getMedian(int) - Method in class moa.evaluation.MeasureCollection
-
- getMemberCliString(int) - Method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- GetMemoryUsage() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getMerit() - Method in class moa.classifiers.rules.multilabel.core.AttributeExpansionSuggestion
-
- getMeritInputAttributes() - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getMeritLowerBound() - Method in class moa.classifiers.trees.iadem.IademAttributeSplitSuggestion
-
- getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
-
- getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
-
- getMeritOfSplit(double[], double[][]) - Method in interface moa.classifiers.core.splitcriteria.SplitCriterion
-
Computes the merit of splitting for a given
ditribution before the split and after it.
- getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
-
- getMeritOfSplit(double[], double[][]) - Method in interface moa.classifiers.rules.core.splitcriteria.AMRulesSplitCriterion
-
- getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRules
-
- getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRulesNode
-
- getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.rules.core.splitcriteria.VarianceRatioSplitCriterion
-
- getMeritOfSplit(double[], double[][]) - Method in class moa.classifiers.rules.core.splitcriteria.VRSplitCriterion
-
- getMeritOfSplit(DoubleVector[], DoubleVector[][]) - Method in class moa.classifiers.multilabel.core.splitcriteria.ICVarianceReduction
-
- getMeritOfSplit(DoubleVector[], DoubleVector[][]) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultilabelInformationGain
-
- getMeritOfSplit(DoubleVector[], DoubleVector[][]) - Method in interface moa.classifiers.rules.multilabel.core.splitcriteria.MultiLabelSplitCriterion
-
- getMeritOfSplit(DoubleVector[], DoubleVector[][]) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultiTargetVarianceRatio
-
- getMeritOfSplitForOutput(DoubleVector[], DoubleVector[][], int) - Method in class moa.classifiers.multilabel.core.splitcriteria.ICVarianceReduction
-
- getMeritOfSplitForOutput(DoubleVector[], DoubleVector[][], int) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultilabelInformationGain
-
- getMeritOfSplitForOutput(DoubleVector[], DoubleVector[][], int) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultiTargetVarianceRatio
-
- getMeritOfSplitForOutput(DoubleVector, DoubleVector[]) - Method in class moa.classifiers.multilabel.core.splitcriteria.ICVarianceReduction
-
- getMeritOfSplitForOutput(DoubleVector, DoubleVector[]) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultilabelInformationGain
-
- getMeritOfSplitForOutput(DoubleVector, DoubleVector[]) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultiTargetVarianceRatio
-
- getMerits() - Method in class moa.classifiers.rules.featureranking.messages.MeritCheckMessage
-
- getMessage() - Method in exception moa.classifiers.trees.iadem.IademException
-
- getMessage() - Method in class moa.streams.clustering.ClusterEvent
-
- getMicroClustering() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- getMicroClusteringResult() - Method in class moa.clusterers.AbstractClusterer
-
- getMicroClusteringResult() - Method in interface moa.clusterers.Clusterer
-
- getMicroClusteringResult() - Method in class moa.clusterers.ClusterGenerator
-
- getMicroClusteringResult() - Method in class moa.clusterers.clustream.Clustream
-
- getMicroClusteringResult() - Method in class moa.clusterers.clustream.WithKmeans
-
- getMicroClusteringResult() - Method in class moa.clusterers.clustree.ClusTree
-
- getMicroClusteringResult() - Method in class moa.clusterers.denstream.WithDBSCAN
-
- getMicroClusteringResult() - Method in class moa.clusterers.kmeanspm.BICO
-
- getMicroClusteringResult() - Method in class moa.clusterers.meta.ConfStream
-
- getMicroClusteringResult() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getMicroClusteringSize() - Method in class moa.clusterers.kmeanspm.BICO
-
Returns the current size of the micro clustering.
- getMicroClusters() - Method in interface moa.clusterers.macro.IDenseMacroCluster
-
- getMicroClusters() - Method in class moa.clusterers.macro.NonConvexCluster
-
- getMiddle(double[]) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance
-
Returns value in the middle of the two parameter values.
- getMinBoxRelWidth() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Gets the minimum relative box width.
- getMinimumValue() - Method in class moa.classifiers.rules.driftdetection.PageHinkleyTest
-
- GetMinPrecNeigh(Long) - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- GetMinPrecNeigh(Long) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- getMinProcessFrequency() - Method in class moa.gui.visualization.ProcessGraphCanvas
-
Returns the minimum process frequency.
- getMinRating() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getMinRating() - Method in interface moa.recommender.rc.data.RecommenderData
-
- getMinValue() - Method in class com.github.javacliparser.FloatOption
-
- getMinValue() - Method in class com.github.javacliparser.IntOption
-
- getMinValue(int) - Method in class moa.evaluation.MeasureCollection
-
- getMinXValue() - Method in class moa.gui.visualization.AbstractGraphCanvas
-
Returns the minimum value for the x-axis.
- getMinXValue() - Method in class moa.gui.visualization.ParamGraphCanvas
-
- getMinXValue() - Method in class moa.gui.visualization.ProcessGraphCanvas
-
- getModel() - Method in class moa.classifiers.AbstractClassifier
-
- getModel() - Method in interface moa.learners.Learner
-
Gets the model if this learner.
- getModelAttIndexToInstanceAttIndex(int, Instance) - Method in class moa.classifiers.rules.AbstractAMRules
-
- getModelContext() - Method in class moa.classifiers.AbstractClassifier
-
- getModelContext() - Method in class moa.clusterers.AbstractClusterer
-
- getModelContext() - Method in interface moa.clusterers.Clusterer
-
- getModelContext() - Method in interface moa.learners.Learner
-
Gets the reference to the header of the data stream.
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.AbstractClassifier
-
Returns a string representation of the model.
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.active.ALRandom
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.active.ALUncertainty
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.bayes.NaiveBayes
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.MajorityClass
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.NoChange
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.Perceptron
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.SGD
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.SGDMultiClass
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.functions.SPegasos
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.lazy.kNN
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.lazy.kNNwithPAW
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.lazy.kNNwithPAWandADWIN
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.lazy.SAMkNN
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.ADACC
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.AdaptiveRandomForest
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.ADOB
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.BOLE
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.DACC
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.DynamicWeightedMajority
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.imbalanced.CSMOTE
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.LearnNSE
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.LeveragingBag
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.LimAttClassifier
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OCBoost
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OnlineSmoothBoost
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OzaBag
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OzaBagAdwin
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OzaBagASHT
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OzaBoost
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.OzaBoostAdwin
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.PairedLearners
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.RandomRules
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.StreamingRandomPatches
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.meta.WEKAClassifier
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.multilabel.MajorityLabelset
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.multilabel.MEKAClassifier
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.MultitargetPerceptron
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.multitarget.BasicMultiLabelLearner
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.multitarget.BasicMultiTargetRegressor
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.multitarget.functions.MultiTargetNoChange
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.oneclass.Autoencoder
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.oneclass.HSTrees
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.oneclass.NearestNeighbourDescription
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.AbstractAMRules
-
print GUI learn model
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.AMRulesRegressorOld
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.BinaryClassifierFromRegressor
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.functions.AdaptiveNodePredictor
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.functions.LowPassFilteredLearner
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.functions.Perceptron
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.functions.TargetMean
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
print GUI learn model
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
print GUI learn model
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.functions.DominantLabelsClassifier
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.rules.RuleClassifier
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.ARFFIMTDD.FIMTDDPerceptron
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.ARFFIMTDD
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.DecisionStump
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.EFDT
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.FIMTDD
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.HoeffdingTree
-
- getModelDescription(StringBuilder, int) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.AbstractClusterer
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.ClusterGenerator
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.clustream.Clustream
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.clustream.WithKmeans
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.clustree.ClusTree
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.CobWeb
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.denstream.WithDBSCAN
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.dstream.Dstream
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.kmeanspm.BICO
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.streamkm.StreamKM
-
- getModelDescription(StringBuilder, int) - Method in class moa.clusterers.WekaClusteringAlgorithm
-
- getModelDescription(StringBuilder, int) - Method in class moa.learners.ChangeDetectorLearner
-
- getModelDescription(StringBuilder, int) - Method in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- getModelDescription(StringBuilder, int) - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTree
-
- getModelDescription(StringBuilder, int) - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTreeEnsemble
-
- getModelDescriptionNoAnomalyDetection(StringBuilder, int) - Method in class moa.classifiers.rules.RuleClassifier
-
- getModelMeasurements() - Method in class moa.classifiers.AbstractClassifier
-
- getModelMeasurements() - Method in class moa.clusterers.AbstractClusterer
-
- getModelMeasurements() - Method in interface moa.clusterers.Clusterer
-
- getModelMeasurements() - Method in interface moa.learners.Learner
-
Gets the current measurements of this learner.
- getModelMeasurementsImpl() - Method in class moa.classifiers.AbstractClassifier
-
Gets the current measurements of this classifier.
The reason for ...Impl methods: ease programmer burden by not requiring
them to remember calls to super in overridden methods.
- getModelMeasurementsImpl() - Method in class moa.classifiers.active.ALRandom
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.active.ALUncertainty
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.bayes.NaiveBayes
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.functions.MajorityClass
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.functions.NoChange
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.functions.Perceptron
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.functions.SGD
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.functions.SGDMultiClass
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.functions.SPegasos
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.lazy.kNN
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.lazy.SAMkNN
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Adds ensemble weights to the measurements.
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Adds ensemble weights to the measurements.
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.ADACC
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.AdaptiveRandomForest
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.ADOB
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.BOLE
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.DACC
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.DynamicWeightedMajority
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.imbalanced.CSMOTE
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.LearnNSE
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.LeveragingBag
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.LimAttClassifier
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OCBoost
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Adds ensemble weights to the measurements.
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OnlineSmoothBoost
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OzaBag
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OzaBagAdwin
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OzaBagASHT
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OzaBoost
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.OzaBoostAdwin
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.PairedLearners
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.RandomRules
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.StreamingRandomPatches
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.meta.WEKAClassifier
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.multilabel.MajorityLabelset
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.multilabel.MEKAClassifier
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.multitarget.BasicMultiLabelLearner
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.multitarget.BasicMultiTargetRegressor
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.multitarget.functions.MultiTargetNoChange
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.oneclass.Autoencoder
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.oneclass.HSTrees
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.oneclass.NearestNeighbourDescription
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.AbstractAMRules
-
print GUI evaluate model
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.BinaryClassifierFromRegressor
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.functions.AdaptiveNodePredictor
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.functions.LowPassFilteredLearner
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.functions.Perceptron
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.functions.TargetMean
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
print GUI evaluate model
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
print GUI evaluate model
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.multilabel.functions.DominantLabelsClassifier
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.rules.RuleClassifier
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.trees.ARFFIMTDD
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.trees.DecisionStump
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.trees.EFDT
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.trees.FIMTDD
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.trees.HoeffdingTree
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- getModelMeasurementsImpl() - Method in class moa.classifiers.trees.ORTO
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.AbstractClusterer
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.ClusterGenerator
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.clustream.Clustream
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.clustream.WithKmeans
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.clustree.ClusTree
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.CobWeb
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.denstream.WithDBSCAN
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.dstream.Dstream
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.kmeanspm.BICO
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.streamkm.StreamKM
-
- getModelMeasurementsImpl() - Method in class moa.clusterers.WekaClusteringAlgorithm
-
- getModelMeasurementsImpl() - Method in class moa.learners.ChangeDetectorLearner
-
- getModelMeasurementsImpl() - Method in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- getModelMeasurementsImpl() - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTree
-
- getModelMeasurementsImpl() - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTreeEnsemble
-
- getModelName() - Method in class moa.classifiers.functions.AdaGrad
-
- getModelName() - Method in class moa.classifiers.functions.SGD
-
- getModelQuality() - Method in class moa.evaluation.CMM_GTAnalysis
-
Calculates the relative number of errors being caused by the underlying cluster model
- getN() - Method in class moa.cluster.CFCluster
-
- getNaiveBayesLimit() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getNaiveBayesPrediction(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNodeNB
-
- getNaiveBayesPrediction(Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNB
-
- getName() - Method in class com.github.javacliparser.AbstractOption
-
- getName() - Method in interface com.github.javacliparser.Option
-
Gets the name of this option
- getName() - Method in class moa.clusterers.clustream.Clustream
-
- getName() - Method in class moa.clusterers.clustream.WithKmeans
-
- getName() - Method in class moa.clusterers.macro.ColorObject
-
- getName() - Method in class moa.core.Measurement
-
- getName() - Method in class moa.gui.experimentertab.ImageChart
-
Return the name.
- getName() - Method in class moa.gui.experimentertab.Measure
-
- getName() - Method in class moa.gui.experimentertab.Stream
-
Returns the name of the stream
- getName(int) - Static method in class moa.clusterers.macro.ColorArray
-
- getName(int) - Method in class moa.evaluation.MeasureCollection
-
- getNames() - Method in class moa.evaluation.Accuracy
-
- getNames() - Method in class moa.evaluation.ALMeasureCollection
-
- getNames() - Method in class moa.evaluation.ChangeDetectionMeasures
-
- getNames() - Method in class moa.evaluation.CMM
-
- getNames() - Method in class moa.evaluation.EntropyCollection
-
- getNames() - Method in class moa.evaluation.F1
-
- getNames() - Method in class moa.evaluation.General
-
- getNames() - Method in class moa.evaluation.MeasureCollection
-
- getNames() - Method in class moa.evaluation.OutlierPerformance
-
- getNames() - Method in class moa.evaluation.RegressionAccuracy
-
- getNames() - Method in class moa.evaluation.Separation
-
- getNames() - Method in class moa.evaluation.SilhouetteCoefficient
-
- getNames() - Method in class moa.evaluation.SSQ
-
- getNames() - Method in class moa.evaluation.StatisticalCollection
-
- getNanoCPUTimeOfCurrentThread() - Static method in class moa.core.TimingUtils
-
- getNanoCPUTimeOfThread(long) - Static method in class moa.core.TimingUtils
-
- getNaNSubstitute() - Method in class moa.tasks.FeatureImportanceConfig
-
- getNbActiveClassifiers() - Method in class moa.classifiers.meta.ADACC
-
- getNbActiveClassifiers() - Method in class moa.classifiers.meta.DACC
-
Returns the number of classifiers used for prediction
which includes the adaptive learners and the snapshots in ADACC
- getNbAdaptiveClassifiers() - Method in class moa.classifiers.meta.ADACC
-
- getNbAdaptiveClassifiers() - Method in class moa.classifiers.meta.DACC
-
Returns the number of adaptive classifiers in the ensemble
which excludes the static snapshots in ADACC
- getNearest(DATA) - Method in class moa.clusterers.outliers.utils.mtree.MTree
-
Performs a nearest-neighbor query on the M-Tree, without constraints.
- getNearest(DATA, double, int) - Method in class moa.clusterers.outliers.utils.mtree.MTree
-
Performs a nearest-neighbor query on the M-Tree, constrained by distance
and/or the number of neighbors.
- getNearestByLimit(DATA, int) - Method in class moa.clusterers.outliers.utils.mtree.MTree
-
Performs a nearest-neighbors query on the M-Tree, constrained by the
number of neighbors.
- getNearestByRange(DATA, double) - Method in class moa.clusterers.outliers.utils.mtree.MTree
-
Performs a nearest-neighbors query on the M-Tree, constrained by distance.
- getNeighbours() - Method in class moa.clusterers.dstream.DensityGrid
-
Generates an Array List of neighbours for this density grid by varying each coordinate
by one in either direction.
- getNewMeasureCollection() - Method in class moa.gui.experimentertab.TaskTextViewerPanel
-
- getNewMeasureCollection() - Method in class moa.gui.TaskTextViewerPanel
-
- getNewRuleFromOtherBranch() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getNewRuleFromOtherOutputs() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getNewSplitNode(long, Iadem2.Node, IademAttributeSplitSuggestion, Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.NominalVirtualNode
-
- getNewSplitNode(long, Iadem2.Node, IademAttributeSplitSuggestion, Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.NumericVirtualNode
-
- getNewSplitNode(long, Iadem2.Node, IademAttributeSplitSuggestion, Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- getNewSplitNode(long, Iadem2.Node, IademAttributeSplitSuggestion, Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveNominalVirtualNode
-
- getNewSplitNode(long, Iadem2.Node, IademAttributeSplitSuggestion, Instance) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveNumericVirtualNode
-
- getNext() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- getNext() - Method in class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
-
- getNextInputIndices(AttributeExpansionSuggestion[]) - Method in interface moa.classifiers.rules.multilabel.inputselectors.InputAttributesSelector
-
- getNextInputIndices(AttributeExpansionSuggestion[]) - Method in class moa.classifiers.rules.multilabel.inputselectors.MeritThreshold
-
- getNextInputIndices(AttributeExpansionSuggestion[]) - Method in class moa.classifiers.rules.multilabel.inputselectors.SelectAllInputs
-
- getNextOutputIndices(DoubleVector[], DoubleVector[], int[]) - Method in class moa.classifiers.rules.multilabel.outputselectors.EntropyThreshold
-
- getNextOutputIndices(DoubleVector[], DoubleVector[], int[]) - Method in interface moa.classifiers.rules.multilabel.outputselectors.OutputAttributesSelector
-
- getNextOutputIndices(DoubleVector[], DoubleVector[], int[]) - Method in class moa.classifiers.rules.multilabel.outputselectors.SelectAllOutputs
-
- getNextOutputIndices(DoubleVector[], DoubleVector[], int[]) - Method in class moa.classifiers.rules.multilabel.outputselectors.StdDevThreshold
-
- getNextOutputIndices(DoubleVector[], DoubleVector[], int[]) - Method in class moa.classifiers.rules.multilabel.outputselectors.VarianceThreshold
-
- getNextPartitionToLeaveOut() - Method in class moa.streams.PartitioningStream
-
get the partition which is excluded from seeing the next instance
- getNode() - Method in class moa.clusterers.clustree.Entry
-
- getNodeCount() - Method in class moa.classifiers.trees.HoeffdingTree
-
- getNodeList() - Method in class moa.classifiers.rules.core.Rule
-
- GetNodesCount() - Method in class moa.clusterers.outliers.MCOD.MicroCluster
-
- getNodeSplitter() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns the splitting method currently in use to split the nodes of the
KDTree.
- getNodeStatistics() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getNoiseLabel() - Method in class moa.gui.visualization.DataPoint
-
- getNoiseSeparability() - Method in class moa.evaluation.CMM_GTAnalysis
-
Calculates how well noise is separable from the given clusters
Small values indicate bad separability, values close to 1 indicate good separability
- getNominalAttClassObserver() - Method in class moa.classifiers.trees.iadem.Iadem2.NominalVirtualNode
-
- getNominalValueString(int, int) - Method in class moa.classifiers.AbstractClassifier
-
Gets the name of a value of an attribute from the header.
- getNominalValueString(int, int) - Method in class moa.clusterers.AbstractClusterer
-
- getNominalValueString(InstancesHeader, int, int) - Static method in class com.yahoo.labs.samoa.instances.InstancesHeader
-
- getNormalizedError(Instance, double) - Method in class moa.classifiers.trees.ARFFIMTDD
-
- getNormalizedError(Instance, double) - Method in class moa.classifiers.trees.FIMTDD
-
- getNormalizedError(MultiLabelInstance, double[]) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- getNormalizedErrors(Prediction, Instance) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getNormalizedErrors(Prediction, Instance) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteralClassification
-
- getNormalizedErrors(Prediction, Instance) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteralRegression
-
- getNormalizedInput(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- getNormalizedOutput(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- getNormalizedPrediction(Instance) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- getNormalizeNodeWidth() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Gets the normalize flag.
- getNrOfClasses() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
Counts the number of classes that are present in the data set.
- getNrOfDimensions() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
-
Returns the number of features (label attribute excluded).
- getNrOfDimensions() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
Return the dimension of the objects in the DataSet.
- getNullString() - Method in class com.github.javacliparser.AbstractClassOption
-
Gets the null string of this option.
- getNullString() - Method in class moa.options.AbstractClassOption
-
Gets the null string of this option.
- getNumberAttributes() - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Gets the number attributes.
- getNumberAttributes() - Method in class moa.classifiers.functions.Perceptron
-
- getNumberChanges() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- getNumberChangesOccurred() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- getNumberClasses() - Method in class moa.classifiers.functions.Perceptron
-
- getNumberDetections() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getNumberDetections() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- getNumberOfCutPoints() - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- getNumberOfCutPoints() - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- getNumberOfCutPoints() - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- getNumberOfCutPoints() - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- getNumberOfGT0Classes() - Method in class moa.evaluation.CMM_GTAnalysis
-
Number of classes/clusters of the new clustering
- getNumberOfInstancesProcessed() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getNumberOfLeaves() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getNumberOfNodes() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getNumberOfNodes(int[]) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getNumberOfNodes(int[]) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getNumberOfNodes(int[]) - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- getNumberOfNodes(int[]) - Method in class moa.classifiers.trees.iadem.Iadem2.NominalVirtualNode
-
- getNumberOfNodes(int[]) - Method in class moa.classifiers.trees.iadem.Iadem2.NumericVirtualNode
-
- getNumberOfNodes(int[]) - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- getNumberOfNodes(int[]) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- getNumberOfSubtrees() - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- getNumberOfSubtrees() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- getNumberOfValues(int) - Method in class moa.evaluation.MeasureCollection
-
- getNumberVotes() - Method in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
-
- getNumberVotes() - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote
-
The number of votes added so far.
- getNumberVotes() - Method in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- getNumberVotes() - Method in interface moa.classifiers.rules.multilabel.core.voting.ErrorWeightedVoteMultiLabel
-
The number of votes added so far.
- getNumberVotes(int) - Method in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- getNumberVotes(int) - Method in interface moa.classifiers.rules.multilabel.core.voting.ErrorWeightedVoteMultiLabel
-
The number of votes for a given output attribute.
- getNumberWarnings() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- getNumBytesWritten() - Method in class com.github.javacliparser.SerializeUtils.ByteCountingOutputStream
-
- getNumBytesWritten() - Method in class moa.core.SerializeUtils.ByteCountingOutputStream
-
- getNumClasses() - Method in class moa.evaluation.MembershipMatrix
-
- getNumClassLabels() - Method in class moa.core.MultilabelInstancesHeader
-
- getNumColors() - Static method in class moa.clusterers.macro.ColorArray
-
- getNumericAttClassObserver() - Method in class moa.classifiers.trees.iadem.Iadem2.NumericVirtualNode
-
- getNumericAttObserver() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getNumericValueString(InstancesHeader, int, double) - Static method in class com.yahoo.labs.samoa.instances.InstancesHeader
-
- getNumFeatures() - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- getNumItems() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getNumItems() - Method in interface moa.recommender.rc.data.RecommenderData
-
- getNumLabels() - Method in class moa.core.MultilabelInstance
-
- getNumLeft() - Method in class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
-
- getNumMeasures() - Method in class moa.evaluation.MeasureCollection
-
- getNumOfTests() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- getNumPoints() - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Returns the number of points of the ClusteringFeature.
- getNumRatings() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getNumRatings() - Method in interface moa.recommender.rc.data.RecommenderData
-
- getNumRootSplits() - Method in class moa.clusterers.clustree.ClusTree
-
Return the number of time the tree has grown in size.
- getNumSplitAttempts() - Method in class moa.classifiers.trees.EFDT.Node
-
- getNumSubtrees() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- getNumSubtrees() - Method in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- getNumSubtrees() - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- getNumSubtrees() - Method in class moa.classifiers.trees.FIMTDD.LeafNode
-
- getNumSubtrees() - Method in class moa.classifiers.trees.FIMTDD.Node
-
- getNumSubtrees() - Method in class moa.classifiers.trees.ORTO.OptionNode
-
- getNumTrees() - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- getNumUsers() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getNumUsers() - Method in interface moa.recommender.rc.data.RecommenderData
-
- getObject(int) - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
Returns the DataObject at the given position.
- getObject(String, String) - Static method in class moa.gui.GUIDefaults
-
Tries to instantiate the class stored for this property, optional
options will be set as well.
- getObject(String, String, Class) - Static method in class moa.gui.GUIDefaults
-
Tries to instantiate the class stored for this property, optional
options will be set as well.
- getObjectInfo() - Method in class moa.gui.visualization.PointPanel
-
- getObjectInfo(Object) - Method in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- getObjectInfo(Object) - Method in class moa.clusterers.outliers.Angiulli.ApproxSTORM
-
- getObjectInfo(Object) - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM
-
- getObjectInfo(Object) - Method in class moa.clusterers.outliers.AnyOut.AnyOut
-
- getObjectInfo(Object) - Method in class moa.clusterers.outliers.MCOD.MCODBase
-
- getObjectInfo(Object) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getObjectInfo(Object) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- getObjectNamed(String) - Method in interface moa.core.ObjectRepository
-
- getObservedClassDistribution() - Method in class moa.classifiers.trees.EFDT.Node
-
- getObservedClassDistribution() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
-
- getObservedClassDistribution() - Method in class moa.classifiers.trees.HoeffdingTree.Node
-
- getObservedClassDistributionAtLeavesReachableThroughThisNode() - Method in class moa.classifiers.trees.HoeffdingTree.Node
-
- getObservedClassDistributionAtLeavesReachableThroughThisNode() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- getOldestEntry() - Method in class moa.core.FixedLengthList
-
- getOption(char) - Method in class com.github.javacliparser.Options
-
- getOption(char, String[]) - Static method in class moa.core.Utils
-
Gets an option indicated by a flag "-Char" from the given array
of strings.
- getOption(String) - Method in class com.github.javacliparser.Options
-
- getOption(String, String[]) - Static method in class moa.core.Utils
-
Gets an option indicated by a flag "-String" from the given array
of strings.
- getOptionArray() - Method in class com.github.javacliparser.Options
-
- getOptionDescriptions() - Method in class com.github.javacliparser.MultiChoiceOption
-
- getOptionLabels() - Method in class com.github.javacliparser.MultiChoiceOption
-
- getOptionPos(char, String[]) - Static method in class moa.core.Utils
-
Gets the index of an option or flag indicated by a flag "-Char" from
the given array of strings.
- getOptionPos(String, String[]) - Static method in class moa.core.Utils
-
Gets the index of an option or flag indicated by a flag "-String" from
the given array of strings.
- getOptions() - Method in class com.github.javacliparser.JavaCLIParser
-
- getOptions() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Gets the current settings of the object.
- getOptions() - Method in class moa.clusterers.outliers.AnyOut.AnyOut
-
- getOptions() - Method in class moa.options.AbstractOptionHandler
-
- getOptions() - Method in interface moa.options.OptionHandler
-
Gets the options of this object
- getOptions() - Method in class moa.tasks.meta.ALMultiParamTask
-
- getOptions() - Method in class weka.classifiers.meta.MOA
-
Gets the current settings of the Classifier.
- getOptions() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Gets the current settings of the datagenerator.
- getOrderingMeasurementName() - Method in class moa.evaluation.preview.LearningCurve
-
- getOrderingName() - Method in class moa.evaluation.preview.PreviewCollection
-
- getOtherBranchLearningLiteral() - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getOtherOutputsLearningLiteral() - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getOutlierer0() - Method in class moa.gui.outliertab.OutlierSetupTab
-
- getOutlierer1() - Method in class moa.gui.outliertab.OutlierSetupTab
-
- getOutlierScore(int) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- GetOutliersFound() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getOutliersResult() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getOutliersVisibility() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- getOutput() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Gets the output state of the change detection.
- getOutput() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector
-
Gets the output state of the change detection.
- getOutputAttributesErrors() - Method in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- getOutputAttributesErrors() - Method in interface moa.classifiers.rules.multilabel.core.voting.ErrorWeightedVoteMultiLabel
-
Returns the weighted error.
- getOutputsCovered() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getOutputsToLearn() - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getOwner() - Method in class moa.classifiers.rules.core.Rule.Builder
-
- getParameter() - Method in class moa.clusterers.meta.BooleanParameter
-
- getParameter() - Method in class moa.clusterers.meta.CategoricalParameter
-
- getParameter() - Method in class moa.clusterers.meta.IntegerParameter
-
- getParameter() - Method in interface moa.clusterers.meta.IParameter
-
- getParameter() - Method in class moa.clusterers.meta.NumericalParameter
-
- getParameter() - Method in class moa.clusterers.meta.OrdinalParameter
-
- getParameterString() - Method in class moa.clusterers.denstream.WithDBSCAN
-
- getParameterString() - Method in class moa.evaluation.CMM_GTAnalysis
-
String with main CMM parameters
- getParameterString() - Method in class moa.evaluation.CMM
-
- getParameterString() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- getParamVector(int) - Method in class moa.clusterers.meta.Algorithm
-
- getParent() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
Return the parent node
- getParent() - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
Return the parent node
- getParent() - Method in class moa.classifiers.trees.EFDT.EFDTLearningNode
-
- getParent() - Method in interface moa.classifiers.trees.EFDT.EFDTNode
-
- getParent() - Method in class moa.classifiers.trees.EFDT.EFDTSplitNode
-
- getParent() - Method in class moa.classifiers.trees.FIMTDD.Node
-
Return the parent node
- getParent() - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- getParentEntry() - Method in class moa.clusterers.clustree.Entry
-
- getPath() - Method in class moa.gui.experimentertab.ReadFile
-
Returns the path of the results.
- getPauseInterval() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- getPauseInterval() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- getPercent() - Method in class moa.classifiers.trees.iadem.Iadem2.NominalVirtualNode
-
- getPercent() - Method in class moa.classifiers.trees.iadem.Iadem2.NumericVirtualNode
-
- getPercent() - Method in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- getPercentInCommon() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getPerceptron() - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- getPerformanceMeasurements() - Method in class moa.evaluation.ALWindowClassificationPerformanceEvaluator
-
- getPerformanceMeasurements() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator
-
- getPerformanceMeasurements() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getPerformanceMeasurements() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- getPerformanceMeasurements() - Method in class moa.evaluation.BasicMultiLabelPerformanceEvaluator
-
- getPerformanceMeasurements() - Method in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- getPerformanceMeasurements() - Method in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- getPerformanceMeasurements() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- getPerformanceMeasurements() - Method in interface moa.evaluation.LearningPerformanceEvaluator
-
Gets the current measurements monitored by this evaluator.
- getPerformanceMeasurements() - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- getPerformanceMeasurements() - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- getPerformanceMeasurements() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator
-
- getPerformanceMeasurements() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- getPoint(int) - Method in class moa.evaluation.CMM_GTAnalysis
-
Get CMM internal point
- getPointColorbyClass(DataPoint, float) - Static method in class moa.gui.visualization.PointPanel
-
- getPointVisibility() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- getPrecisionStatistic() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getPrecisionStatistic(int) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getPredicate() - Method in class moa.classifiers.rules.multilabel.core.AttributeExpansionSuggestion
-
- getPrediction() - Method in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- getPrediction() - Method in interface moa.classifiers.rules.multilabel.core.voting.ErrorWeightedVoteMultiLabel
-
- getPrediction(Instance) - Method in class moa.classifiers.rules.core.Rule
-
- getPrediction(Instance) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getPrediction(Instance) - Method in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- getPrediction(Instance) - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- getPrediction(Instance) - Method in class moa.classifiers.trees.ARFFIMTDD.SplitNode
-
- getPrediction(Instance) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
-
- getPrediction(Instance) - Method in class moa.classifiers.trees.FIMTDD.Node
-
- getPrediction(Instance) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
-
- getPrediction(Instance, int) - Method in class moa.classifiers.rules.core.Rule
-
- getPrediction(Instance, int) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getPrediction(Instance, int) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- getPrediction(Instance, ORTO) - Method in class moa.classifiers.trees.ORTO.OptionNode
-
- getPrediction(MultiLabelInstance) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.LeafNode
-
- getPrediction(MultiLabelInstance) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- getPrediction(MultiLabelInstance) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.SplitNode
-
- getPredictionError() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- getPredictionForInstance(Instance) - Method in class moa.classifiers.AbstractClassifier
-
- getPredictionForInstance(Instance) - Method in class moa.classifiers.AbstractMultiLabelLearner
-
- getPredictionForInstance(Instance) - Method in interface moa.classifiers.Classifier
-
Gets the reference to the header of the data stream.
- getPredictionForInstance(Instance, HoeffdingTree) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.AbstractMultiLabelLearner
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.multilabel.MajorityLabelset
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.multilabel.MEKAClassifier
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.multilabel.meta.OzaBagAdwinML
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.multilabel.meta.OzaBagML
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- getPredictionForInstance(MultiLabelInstance) - Method in interface moa.classifiers.MultiLabelLearner
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.multitarget.BasicMultiLabelLearner
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.multitarget.BasicMultiTargetRegressor
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.multitarget.functions.MultiTargetNoChange
-
- getPredictionForInstance(MultiLabelInstance) - Method in interface moa.classifiers.MultiTargetLearnerSemiSupervised
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.functions.DominantLabelsClassifier
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- getPredictionForInstance(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- getPredictionForInstance(E) - Method in interface moa.learners.Learner
-
- getPredictionForInstance(Example<Instance>) - Method in class moa.classifiers.AbstractClassifier
-
- getPredictionForInstance(Example<Instance>) - Method in class moa.classifiers.AbstractMultiLabelLearner
-
- getPredictionForInstance(Example<Instance>) - Method in class moa.classifiers.multilabel.meta.OzaBagAdwinML
-
- getPredictionForInstance(Example<Instance>) - Method in class moa.classifiers.multilabel.meta.OzaBagML
-
- getPredictionForInstance(Example<Instance>) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
-
- getPredictionModel(Instance) - Method in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
Retrieve the class votes using the perceptron learner
- getPredictionModel(Instance) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
-
Retrieve the class votes using the perceptron learner
- getPredictionModel(MultiLabelInstance) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.LeafNode
-
Retrieve the class votes using the perceptron learner
- getPredictionTargetMean(Instance) - Method in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- getPredictionTargetMean(Instance) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
-
- getPredictionTargetMean(MultiLabelInstance) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.LeafNode
-
- getPreferredScrollableViewportSize() - Method in class moa.gui.featureanalysis.AttributeSelectionPanel
-
- getPreferredScrollableViewportSize() - Method in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
- getPreferredSize() - Method in class moa.gui.visualization.GraphCurve
-
- getPreMaterializedObject() - Method in class moa.options.AbstractClassOption
-
Returns the current object.
- getPreparedClassOption(ClassOption) - Method in class moa.options.AbstractOptionHandler
-
Gets a prepared option of this class.
- getPreparedClassOption(ClassOption) - Method in class moa.options.OptionsHandler
-
Gets a prepared option of this class.
- getPreview(ResultPreviewListener) - Method in class moa.gui.experimentertab.ExpTaskThread
-
- getPreview(ResultPreviewListener) - Method in class moa.tasks.TaskThread
-
- getPreviews() - Method in class moa.evaluation.preview.PreviewCollection
-
- getPrevious() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- getProbability(double, double, double) - Method in class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.CantellisInequality
-
- getProbability(double, double, double) - Method in class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.ChebyshevInequality
-
- getProbability(double, double, double) - Method in class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.GaussInequality
-
- getProbability(double, double, double) - Method in interface moa.classifiers.rules.core.anomalydetection.probabilityfunctions.ProbabilityFunction
-
- getProcessFrequencies() - Method in class moa.gui.visualization.ProcessGraphCanvas
-
Returns the list of registered process frequencies.
- getProcessFrequency() - Method in class moa.gui.visualization.GraphCanvas
-
- getProgressBar() - Method in class moa.tasks.FeatureImportanceConfig
-
- getProgressFraction() - Method in class moa.core.InputStreamProgressMonitor
-
- getProperties() - Static method in class moa.gui.GUIDefaults
-
returns the associated properties file.
- getPropotionBelow(double) - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- getPurpose() - Method in class com.github.javacliparser.AbstractOption
-
- getPurpose() - Method in interface com.github.javacliparser.Option
-
Gets the purpose of this option
- getPurposeString() - Method in class com.github.javacliparser.JavaCLIParser
-
- getPurposeString() - Method in class moa.classifiers.AbstractClassifier
-
- getPurposeString() - Method in class moa.classifiers.active.ALRandom
-
- getPurposeString() - Method in class moa.classifiers.active.ALUncertainty
-
- getPurposeString() - Method in class moa.classifiers.active.budget.FixedBM
-
- getPurposeString() - Method in class moa.classifiers.bayes.NaiveBayes
-
- getPurposeString() - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
-
- getPurposeString() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- getPurposeString() - Method in class moa.classifiers.functions.AdaGrad
-
- getPurposeString() - Method in class moa.classifiers.functions.MajorityClass
-
- getPurposeString() - Method in class moa.classifiers.functions.NoChange
-
- getPurposeString() - Method in class moa.classifiers.functions.Perceptron
-
- getPurposeString() - Method in class moa.classifiers.functions.SGD
-
- getPurposeString() - Method in class moa.classifiers.functions.SGDMultiClass
-
- getPurposeString() - Method in class moa.classifiers.functions.SPegasos
-
- getPurposeString() - Method in class moa.classifiers.lazy.kNN
-
- getPurposeString() - Method in class moa.classifiers.lazy.kNNwithPAW
-
- getPurposeString() - Method in class moa.classifiers.lazy.kNNwithPAWandADWIN
-
- getPurposeString() - Method in class moa.classifiers.lazy.SAMkNN
-
- getPurposeString() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- getPurposeString() - Method in class moa.classifiers.meta.ADACC
-
- getPurposeString() - Method in class moa.classifiers.meta.AdaptiveRandomForest
-
- getPurposeString() - Method in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- getPurposeString() - Method in class moa.classifiers.meta.ADOB
-
- getPurposeString() - Method in class moa.classifiers.meta.BOLE
-
- getPurposeString() - Method in class moa.classifiers.meta.DACC
-
- getPurposeString() - Method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- getPurposeString() - Method in class moa.classifiers.meta.imbalanced.CSMOTE
-
- getPurposeString() - Method in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- getPurposeString() - Method in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- getPurposeString() - Method in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- getPurposeString() - Method in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- getPurposeString() - Method in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- getPurposeString() - Method in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- getPurposeString() - Method in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- getPurposeString() - Method in class moa.classifiers.meta.LeveragingBag
-
- getPurposeString() - Method in class moa.classifiers.meta.LimAttClassifier
-
- getPurposeString() - Method in class moa.classifiers.meta.OCBoost
-
- getPurposeString() - Method in class moa.classifiers.meta.OnlineSmoothBoost
-
- getPurposeString() - Method in class moa.classifiers.meta.OzaBag
-
- getPurposeString() - Method in class moa.classifiers.meta.OzaBagAdwin
-
- getPurposeString() - Method in class moa.classifiers.meta.OzaBagASHT
-
- getPurposeString() - Method in class moa.classifiers.meta.OzaBoost
-
- getPurposeString() - Method in class moa.classifiers.meta.OzaBoostAdwin
-
- getPurposeString() - Method in class moa.classifiers.meta.RandomRules
-
- getPurposeString() - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
-
- getPurposeString() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- getPurposeString() - Method in class moa.classifiers.meta.WEKAClassifier
-
- getPurposeString() - Method in class moa.classifiers.multilabel.MajorityLabelset
-
- getPurposeString() - Method in class moa.classifiers.multilabel.MEKAClassifier
-
- getPurposeString() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- getPurposeString() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.MultitargetPerceptron
-
- getPurposeString() - Method in class moa.classifiers.multitarget.functions.MultiTargetNoChange
-
- getPurposeString() - Method in class moa.classifiers.oneclass.Autoencoder
-
- getPurposeString() - Method in class moa.classifiers.oneclass.HSTrees
-
- getPurposeString() - Method in class moa.classifiers.oneclass.NearestNeighbourDescription
-
- getPurposeString() - Method in class moa.classifiers.rules.core.anomalydetection.NoAnomalyDetection
-
- getPurposeString() - Method in class moa.classifiers.rules.core.changedetection.NoChangeDetection
-
- getPurposeString() - Method in class moa.classifiers.rules.functions.AdaptiveNodePredictor
-
- getPurposeString() - Method in class moa.classifiers.rules.functions.LowPassFilteredLearner
-
- getPurposeString() - Method in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelClassifier
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiTargetRegressorSemiSuper
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultilabelInformationGain
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.functions.MultiLabelNaiveBayes
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.functions.MultiLabelPerceptronClassification
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.functions.MultiTargetMeanRegressor
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.functions.MultiTargetPerceptronRegressor
-
- getPurposeString() - Method in class moa.classifiers.rules.multilabel.outputselectors.EntropyThreshold
-
- getPurposeString() - Method in class moa.classifiers.rules.RuleClassifier
-
- getPurposeString() - Method in class moa.classifiers.trees.AdaHoeffdingOptionTree
-
- getPurposeString() - Method in class moa.classifiers.trees.ARFFIMTDD.FIMTDDPerceptron
-
- getPurposeString() - Method in class moa.classifiers.trees.ARFFIMTDD
-
- getPurposeString() - Method in class moa.classifiers.trees.ARFHoeffdingTree
-
- getPurposeString() - Method in class moa.classifiers.trees.ASHoeffdingTree
-
- getPurposeString() - Method in class moa.classifiers.trees.DecisionStump
-
- getPurposeString() - Method in class moa.classifiers.trees.EFDT
-
- getPurposeString() - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
-
- getPurposeString() - Method in class moa.classifiers.trees.FIMTDD
-
- getPurposeString() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
-
- getPurposeString() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- getPurposeString() - Method in class moa.classifiers.trees.HoeffdingTree
-
- getPurposeString() - Method in class moa.classifiers.trees.LimAttHoeffdingTree
-
- getPurposeString() - Method in class moa.classifiers.trees.ORTO
-
- getPurposeString() - Method in class moa.classifiers.trees.RandomHoeffdingTree
-
- getPurposeString() - Method in class moa.clusterers.AbstractClusterer
-
- getPurposeString() - Method in class moa.clusterers.outliers.AnyOut.AnyOut
-
- getPurposeString() - Method in class moa.clusterers.WekaClusteringAlgorithm
-
- getPurposeString() - Method in class moa.gui.experimentertab.tasks.EvaluateConceptDrift
-
- getPurposeString() - Method in class moa.gui.experimentertab.tasks.EvaluateInterleavedChunks
-
- getPurposeString() - Method in class moa.gui.experimentertab.tasks.EvaluateInterleavedTestThenTrain
-
- getPurposeString() - Method in class moa.gui.experimentertab.tasks.EvaluatePeriodicHeldOutTest
-
- getPurposeString() - Method in class moa.gui.experimentertab.tasks.EvaluatePrequential
-
- getPurposeString() - Method in class moa.gui.experimentertab.tasks.EvaluatePrequentialCV
-
- getPurposeString() - Method in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- getPurposeString() - Method in class moa.options.AbstractOptionHandler
-
Dictionary with option texts and objects
- getPurposeString() - Method in interface moa.options.OptionHandler
-
Gets the purpose of this object
- getPurposeString() - Method in class moa.recommender.dataset.impl.FlixsterDataset
-
- getPurposeString() - Method in class moa.recommender.dataset.impl.JesterDataset
-
- getPurposeString() - Method in class moa.recommender.dataset.impl.MovielensDataset
-
- getPurposeString() - Method in class moa.streams.ArffFileStream
-
- getPurposeString() - Method in class moa.streams.clustering.FileStream
-
- getPurposeString() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- getPurposeString() - Method in class moa.streams.clustering.SimpleCSVStream
-
- getPurposeString() - Method in class moa.streams.ConceptDriftRealStream
-
- getPurposeString() - Method in class moa.streams.ConceptDriftStream
-
- getPurposeString() - Method in class moa.streams.FilteredStream
-
- getPurposeString() - Method in class moa.streams.filters.AddNoiseFilter
-
- getPurposeString() - Method in class moa.streams.filters.RBFFilter
-
- getPurposeString() - Method in class moa.streams.filters.ReLUFilter
-
- getPurposeString() - Method in class moa.streams.filters.RemoveDiscreteAttributeFilter
-
- getPurposeString() - Method in class moa.streams.filters.ReplacingMissingValuesFilter
-
- getPurposeString() - Method in class moa.streams.filters.SelectAttributesFilter
-
- getPurposeString() - Method in class moa.streams.generators.AgrawalGenerator
-
- getPurposeString() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- getPurposeString() - Method in class moa.streams.generators.HyperplaneGenerator
-
- getPurposeString() - Method in class moa.streams.generators.LEDGenerator
-
- getPurposeString() - Method in class moa.streams.generators.LEDGeneratorDrift
-
- getPurposeString() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- getPurposeString() - Method in class moa.streams.generators.multilabel.MultilabelArffFileStream
-
- getPurposeString() - Method in class moa.streams.generators.RandomRBFGenerator
-
- getPurposeString() - Method in class moa.streams.generators.RandomRBFGeneratorDrift
-
- getPurposeString() - Method in class moa.streams.generators.RandomTreeGenerator
-
- getPurposeString() - Method in class moa.streams.generators.SEAGenerator
-
- getPurposeString() - Method in class moa.streams.generators.STAGGERGenerator
-
- getPurposeString() - Method in class moa.streams.generators.WaveformGenerator
-
- getPurposeString() - Method in class moa.streams.generators.WaveformGeneratorDrift
-
- getPurposeString() - Method in class moa.streams.MultiFilteredStream
-
- getPurposeString() - Method in class moa.streams.MultiLabelFilteredStream
-
- getPurposeString() - Method in class moa.streams.MultiTargetArffFileStream
-
- getPurposeString() - Method in class moa.streams.RecurrentConceptDriftStream
-
- getPurposeString() - Method in class moa.tasks.CacheShuffledStream
-
- getPurposeString() - Method in class moa.tasks.EvaluateClustering
-
- getPurposeString() - Method in class moa.tasks.EvaluateConceptDrift
-
- getPurposeString() - Method in class moa.tasks.EvaluateInterleavedChunks
-
- getPurposeString() - Method in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- getPurposeString() - Method in class moa.tasks.EvaluateModel
-
- getPurposeString() - Method in class moa.tasks.EvaluateModelMultiLabel
-
- getPurposeString() - Method in class moa.tasks.EvaluateModelMultiTarget
-
- getPurposeString() - Method in class moa.tasks.EvaluateModelRegression
-
- getPurposeString() - Method in class moa.tasks.EvaluateMultipleClusterings
-
- getPurposeString() - Method in class moa.tasks.EvaluateOnlineRecommender
-
- getPurposeString() - Method in class moa.tasks.EvaluatePeriodicHeldOutTest
-
- getPurposeString() - Method in class moa.tasks.EvaluatePrequential
-
- getPurposeString() - Method in class moa.tasks.EvaluatePrequentialCV
-
- getPurposeString() - Method in class moa.tasks.EvaluatePrequentialDelayed
-
- getPurposeString() - Method in class moa.tasks.EvaluatePrequentialDelayedCV
-
- getPurposeString() - Method in class moa.tasks.EvaluatePrequentialMultiLabel
-
- getPurposeString() - Method in class moa.tasks.EvaluatePrequentialMultiTarget
-
- getPurposeString() - Method in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- getPurposeString() - Method in class moa.tasks.EvaluatePrequentialRegression
-
- getPurposeString() - Method in class moa.tasks.FeatureImportanceConfig
-
- getPurposeString() - Method in class moa.tasks.LearnModel
-
- getPurposeString() - Method in class moa.tasks.LearnModelMultiLabel
-
- getPurposeString() - Method in class moa.tasks.LearnModelMultiTarget
-
- getPurposeString() - Method in class moa.tasks.LearnModelRegression
-
- getPurposeString() - Method in class moa.tasks.MeasureStreamSpeed
-
- getPurposeString() - Method in class moa.tasks.meta.ALMultiParamTask
-
- getPurposeString() - Method in class moa.tasks.meta.ALPartitionEvaluationTask
-
- getPurposeString() - Method in class moa.tasks.meta.ALPrequentialEvaluationTask
-
- getPurposeString() - Method in class moa.tasks.Plot
-
- getPurposeString() - Method in class moa.tasks.RunStreamTasks
-
- getPurposeString() - Method in class moa.tasks.RunTasks
-
- getPurposeString() - Method in class moa.tasks.WriteConfigurationToJupyterNotebook
-
Gets the purpose of this object
- getPurposeString() - Method in class moa.tasks.WriteMultipleStreamsToARFF
-
- getPurposeString() - Method in class moa.tasks.WriteStreamToARFFFile
-
- getQuantile(double) - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- getRadii() - Method in class moa.clusterers.streamkm.CoresetCostTriple
-
- getRadius() - Method in class moa.cluster.CFCluster
-
See interface Cluster
- getRadius() - Method in class moa.cluster.SphereCluster
-
- getRadius() - Method in class moa.clusterers.clustream.ClustreamKernel
-
- getRadius() - Method in class moa.clusterers.clustree.ClusKernel
-
See interface Cluster
- getRadius() - Method in class moa.clusterers.denstream.MicroCluster
-
- getRadius() - Method in class moa.clusterers.dstream.DensityGrid
-
Provides the radius of a density grid.
- getRadius() - Method in class moa.clusterers.macro.NonConvexCluster
-
- getRadius(long) - Method in class moa.clusterers.denstream.MicroCluster
-
- getRange() - Method in class com.github.javacliparser.RangeOption
-
- getRange() - Method in class moa.clusterers.meta.BooleanParameter
-
- getRange() - Method in class moa.clusterers.meta.CategoricalParameter
-
- getRangeOfMerit(double[]) - Method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
-
- getRangeOfMerit(double[]) - Method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
-
- getRangeOfMerit(double[]) - Method in interface moa.classifiers.core.splitcriteria.SplitCriterion
-
Computes the range of splitting merit
- getRangeOfMerit(double[]) - Method in class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
-
- getRangeOfMerit(double[]) - Method in interface moa.classifiers.rules.core.splitcriteria.AMRulesSplitCriterion
-
- getRangeOfMerit(double[]) - Method in class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRules
-
- getRangeOfMerit(double[]) - Method in class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRulesNode
-
- getRangeOfMerit(double[]) - Method in class moa.classifiers.rules.core.splitcriteria.VarianceRatioSplitCriterion
-
- getRangeOfMerit(DoubleVector[]) - Method in class moa.classifiers.multilabel.core.splitcriteria.ICVarianceReduction
-
- getRangeOfMerit(DoubleVector[]) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultilabelInformationGain
-
- getRangeOfMerit(DoubleVector[]) - Method in interface moa.classifiers.rules.multilabel.core.splitcriteria.MultiLabelSplitCriterion
-
- getRangeOfMerit(DoubleVector[]) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultiTargetVarianceRatio
-
- getRanges() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Method to get the ranges.
- getRankAlg() - Method in class moa.gui.experimentertab.statisticaltests.StatisticalTest
-
Return the ranking of the algorithms.
- getRating(int, int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getRating(int, int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- getRatingsItem(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getRatingsItem(int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- getRatingsUser(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getRatingsUser(int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- getRatio() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- getRatio() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- getRawLevel() - Method in class moa.clusterers.clustree.Node
-
Return the level number in the node.
- getRecall() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- getRecall() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- getRecallStatistic() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getRecallStatistic(int) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getRelationName() - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- getRelationName() - Method in class com.yahoo.labs.samoa.instances.Instances
-
Gets the relation name.
- getRelevanceStamp() - Method in class moa.clusterers.clustream.ClustreamKernel
-
- getRelevantLabels(Instance) - Static method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
-
- getRelevantLabels(Instance) - Method in class moa.core.utils.Converter
-
- getRelNumOfAcqInst() - Method in class moa.evaluation.ALWindowClassificationPerformanceEvaluator
-
Returns relative number of acquired labels so far.
- getRemoveTime() - Method in class moa.clusterers.dstream.CharacteristicVector
-
- getRequiredType() - Method in class com.github.javacliparser.AbstractClassOption
-
Gets the class type of this option.
- getRequiredType() - Method in class moa.options.AbstractClassOption
-
Gets the class type of this option.
- getResultingNodeStatistics() - Method in class moa.classifiers.rules.multilabel.core.AttributeExpansionSuggestion
-
- getResultsFolder() - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- getRevision() - Method in class weka.classifiers.meta.MOA
-
Returns the revision string.
- getRevision() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Returns the revision string.
- getRightStreamPanel() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- getRightStreamPanel() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- getRowCount() - Method in class moa.gui.active.ALTaskManagerPanel.TaskTableModel
-
- getRowCount() - Method in class moa.gui.AuxiliarTaskManagerPanel.TaskTableModel
-
- getRowCount() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
-
- getRowCount() - Method in class moa.gui.experimentertab.TaskManagerTabPanel.TaskTableModel
-
- getRowCount() - Method in class moa.gui.LineGraphViewPanel.PlotTableModel
-
- getRowCount() - Method in class moa.gui.MultiLabelTaskManagerPanel.TaskTableModel
-
- getRowCount() - Method in class moa.gui.MultiTargetTaskManagerPanel.TaskTableModel
-
- getRowCount() - Method in class moa.gui.PreviewTableModel
-
- getRowCount() - Method in class moa.gui.RegressionTaskManagerPanel.TaskTableModel
-
- getRowCount() - Method in class moa.gui.TaskManagerPanel.TaskTableModel
-
- getRuleMajorityClassIndex(RuleClassification) - Method in class moa.classifiers.rules.RuleClassifier
-
- getRuleNumberID() - Method in class moa.classifiers.rules.core.Rule
-
- getRuleNumberID() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getSampleMean() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Reservoir
-
- getSaveExperimentsPath() - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- getSaveInstanceData() - Method in class moa.clusterers.CobWeb
-
Get the value of saveInstances.
- getScoredAUC() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- getScoredAUC() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- getScreenSize() - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
Get the screen size so that the amplified graph size is the same as the screen size.
- getSecond() - Method in class moa.recommender.rc.utils.Pair
-
- getSelectedAttributes() - Method in class moa.gui.featureanalysis.AttributeSelectionPanel
-
Gets an array containing the indices of all selected attributes.
- getSelectedAttributes() - Method in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
Gets an array containing the indices of all selected attributes.
- getSelectedCurrenTask() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- getSelectedMeasures() - Method in class moa.gui.clustertab.ClusteringEvalPanel
-
- getSelectedMeasures() - Method in class moa.gui.outliertab.OutlierEvalPanel
-
- getSelectedPlotItem() - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- getSelectedPlotTyeIndex() - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- getSelectedTasks() - Method in class moa.gui.active.ALTaskManagerPanel
-
- getSelectedTasks() - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- getSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- getSelectedTasks() - Method in class moa.gui.experimentertab.TaskManagerTabPanel
-
- getSelectedTasks() - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- getSelectedTasks() - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- getSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
-
- getSelectedTasks() - Method in class moa.gui.TaskManagerPanel
-
- getSelectionModel() - Method in class moa.gui.featureanalysis.AttributeSelectionPanel
-
Gets the selection model used by the table.
- getSelectionModel() - Method in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
Gets the selection model used by the table.
- getShapeToPlot() - Method in class moa.gui.LineGraphViewPanel.PlotLine
-
- getShowZeroInstancesAsUnknown() - Method in class moa.gui.featureanalysis.InstancesSummaryPanel
-
Get whether to show zero instances as unknown (i.e.
- getSimplePrediction() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getSimplePrediction() - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- getSingleLineDescription(StringBuilder) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- getSingleLineDescription(StringBuilder) - Method in class moa.core.DoubleVector
-
- getSingleLineDescription(StringBuilder, int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- getSingleLineDescription(StringBuilder, int) - Method in class moa.core.DoubleVector
-
- getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Return if single mode is set for the given data generator
mode depends on option setting and or generator type.
- getSize() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- getSize() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Reservoir
-
- getSkipIdentical() - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch
-
Gets whether if identical instances are skipped from the neighbourhood.
- GetSpeed() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- getSplitDim() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
Gets the splitting dimension.
- getSplitIndex() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getSplitMeasureOptions() - Static method in class moa.classifiers.trees.iadem.IademSplitCriterion
-
- getSplitMeasureText() - Method in class moa.classifiers.trees.iadem.IademSplitCriterion
-
- getSplitPointSuggestions() - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- getSplitTest() - Method in class moa.classifiers.rules.core.RuleSplitNode
-
- getSplitTest() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- getSplitTest() - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- getSplitValue() - Method in class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
-
- getSplitValue() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
Gets the splitting value.
- getSplitValue() - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- getSquareError() - Method in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- getSquareError() - Method in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- getSquareError() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- getSquareError() - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- getSquareError() - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- getSquareError() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- getStackTraceString(Exception) - Static method in class moa.core.MiscUtils
-
- getStart() - Method in class com.yahoo.labs.samoa.instances.Range
-
- getStart(int) - Method in class moa.streams.filters.Selection
-
- getStateString() - Method in class com.github.javacliparser.AbstractOption
-
- getStateString() - Method in class com.github.javacliparser.FlagOption
-
- getStateString() - Method in interface com.github.javacliparser.Option
-
Gets the state of this option in human readable form
- getStaticOutput() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getStaticOutput(InstanceInformation) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getStaticOutput(InstanceInformation) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteralClassification
-
- getStaticOutput(InstanceInformation) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteralRegression
-
- getStatistics() - Method in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- getStatistics() - Method in class moa.clusterers.outliers.Angiulli.STORMBase
-
- getStatistics() - Method in class moa.clusterers.outliers.AnyOut.AnyOut
-
- getStatistics() - Method in class moa.clusterers.outliers.MCOD.MCODBase
-
- getStatistics() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getStatistics() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- getStatisticsBranchSplit() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getStatisticsNewRuleActiveLearningNode() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getStatisticsOtherBranchSplit() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- getStd() - Method in class moa.gui.experimentertab.Measure
-
Returns the standard deviation
- getStdDev() - Method in class moa.core.GaussianEstimator
-
- getStdPreviews() - Method in class moa.evaluation.preview.MeanPreviewCollection
-
- getStream() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- getStream() - Method in class moa.gui.experimentertab.ReadFile
-
Returns the name of the streams.
- getStream() - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- getStream0() - Method in class moa.gui.clustertab.ClusteringSetupTab
-
- getStream0() - Method in class moa.gui.outliertab.OutlierSetupTab
-
- getStreams() - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- getStreamsID() - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- getStreamValueAsCLIString() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- getStreamValueAsCLIString() - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- getStringValues() - Static method in enum moa.tasks.Plot.LegendLocation
-
Get string values for the enum values.
- getStringValues() - Static method in enum moa.tasks.Plot.LegendType
-
Get string values for the enum values.
- getStringValues() - Static method in enum moa.tasks.Plot.PlotStyle
-
Get string values for the enum values.
- getStringValues() - Static method in enum moa.tasks.Plot.Terminal
-
Get string values for the enum values.
- getStructure() - Method in class com.yahoo.labs.samoa.instances.ArffLoader
-
Gets the structure.
- getSubClassifiers() - Method in class moa.classifiers.AbstractClassifier
-
- getSubClassifiers() - Method in interface moa.classifiers.Classifier
-
Gets the classifiers of this ensemble.
- getSubClassifiers() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
- getSubClassifiers() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- getSubClassifiers() - Method in class moa.classifiers.meta.ADOB
-
- getSubClassifiers() - Method in class moa.classifiers.meta.BOLE
-
- getSubClassifiers() - Method in class moa.classifiers.meta.DACC
-
- getSubClassifiers() - Method in class moa.classifiers.meta.LeveragingBag
-
- getSubClassifiers() - Method in class moa.classifiers.meta.LimAttClassifier
-
- getSubClassifiers() - Method in class moa.classifiers.meta.OCBoost
-
- getSubClassifiers() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
- getSubClassifiers() - Method in class moa.classifiers.meta.OnlineSmoothBoost
-
- getSubClassifiers() - Method in class moa.classifiers.meta.OzaBag
-
- getSubClassifiers() - Method in class moa.classifiers.meta.OzaBagAdwin
-
- getSubClassifiers() - Method in class moa.classifiers.meta.OzaBagASHT
-
- getSubClassifiers() - Method in class moa.classifiers.meta.OzaBoost
-
- getSubClassifiers() - Method in class moa.classifiers.meta.OzaBoostAdwin
-
- getSubClassifiers() - Method in class moa.classifiers.meta.RandomRules
-
- getSubClassifiers() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- getSubClassifiers() - Method in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- getSubClusterers() - Method in class moa.clusterers.AbstractClusterer
-
- getSubClusterers() - Method in interface moa.clusterers.Clusterer
-
- getSublearners() - Method in class moa.classifiers.AbstractClassifier
-
- getSublearners() - Method in class moa.classifiers.meta.AdaptiveRandomForest
-
- getSublearners() - Method in class moa.classifiers.meta.StreamingRandomPatches
-
- getSublearners() - Method in interface moa.learners.Learner
-
Gets the learners of this ensemble.
- getSubtaskLevel() - Method in class moa.tasks.meta.MetaMainTask
-
Get the tasks subtask level (how deep it is in the tree).
- getSubtaskThreads() - Method in class moa.tasks.meta.ALMainTask
-
- getSubtaskThreads() - Method in class moa.tasks.meta.ALMultiParamTask
-
- getSubtaskThreads() - Method in class moa.tasks.meta.ALPartitionEvaluationTask
-
- getSubtaskThreads() - Method in class moa.tasks.meta.ALPrequentialEvaluationTask
-
- getSubtaskThreads() - Method in class moa.tasks.meta.MetaMainTask
-
Get the list of threads for all subtasks and recursively the children's
subtasks.
- getSubtreeNodeCount() - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getSubtreeNodeCount() - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- getSubtreeNodeCount() - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- getSubtreeNodeCount() - Method in class moa.classifiers.trees.iadem.Iadem2.VirtualNode
-
- getSubtreeNodeCount() - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- getSuggestedCutpoints() - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- getSumPoints() - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Returns the sum of points of the ClusteringFeature.
- getSumSquaredLength() - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Returns the sum of the squared lengths of the ClusteringFeature.
- getSVGString(int) - Method in class moa.gui.visualization.ClusterPanel
-
- getSVGString(int) - Method in class moa.gui.visualization.OutlierPanel
-
- getSVGString(int) - Method in class moa.gui.visualization.PointPanel
-
- getSymbol() - Method in class moa.classifiers.rules.Predicates
-
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.active.ALTaskManagerPanel.ProgressCellRenderer
-
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.active.ALTaskManagerPanel.TaskColorCodingCellRenderer
-
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.AuxiliarTaskManagerPanel.ProgressCellRenderer
-
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.ProgressCellRenderer
-
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.experimentertab.TaskManagerTabPanel.ProgressCellRenderer
-
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.MultiLabelTaskManagerPanel.ProgressCellRenderer
-
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.MultiTargetTaskManagerPanel.ProgressCellRenderer
-
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.RegressionTaskManagerPanel.ProgressCellRenderer
-
- getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class moa.gui.TaskManagerPanel.ProgressCellRenderer
-
- getTableModel() - Method in class moa.gui.featureanalysis.AttributeSelectionPanel
-
Get the table model in use (or null if no instances have been set yet).
- getTableModel() - Method in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
Get the table model in use (or null if no instances have been set yet).
- getTabs() - Static method in class moa.gui.GUIDefaults
-
returns an array with the classnames of all the additional panels to
display as tabs in the GUI.
- getTabTitle() - Method in class moa.gui.AbstractTabPanel
-
Returns the string to display as title of the tab.
- getTabTitle() - Method in class moa.gui.ALTabPanel
-
- getTabTitle() - Method in class moa.gui.AuxiliarTabPanel
-
- getTabTitle() - Method in class moa.gui.ClassificationTabPanel
-
- getTabTitle() - Method in class moa.gui.clustertab.ClusteringTabPanel
-
- getTabTitle() - Method in class moa.gui.ConceptDriftTabPanel
-
- getTabTitle() - Method in class moa.gui.experimentertab.ExperimenterTabPanel
-
- getTabTitle() - Method in class moa.gui.featureanalysis.FeatureAnalysisTabPanel
-
- getTabTitle() - Method in class moa.gui.MultiLabelTabPanel
-
- getTabTitle() - Method in class moa.gui.MultiTargetTabPanel
-
- getTabTitle() - Method in class moa.gui.outliertab.OutlierTabPanel
-
- getTabTitle() - Method in class moa.gui.RegressionTabPanel
-
- getTabTitle() - Method in class moa.gui.ScriptingTabPanel
-
Returns the string to display as title of the tab.
- getTail() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- getTargetMean() - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- getTargetMeanError() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- getTargetSquareError() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- getTask() - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- getTask() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- getTask() - Method in class moa.tasks.TaskThread
-
- getTaskClass() - Method in class moa.evaluation.preview.LearningCurve
-
- getTaskClass() - Method in class moa.evaluation.preview.Preview
-
- getTaskClass() - Method in class moa.evaluation.preview.PreviewCollection
-
- getTaskClass() - Method in class moa.evaluation.preview.PreviewCollectionLearningCurveWrapper
-
- getTaskName() - Method in class moa.tasks.AbstractTask
-
Gets the name of this task.
- getTaskResultType() - Method in class moa.gui.experimentertab.tasks.EvaluateConceptDrift
-
- getTaskResultType() - Method in class moa.gui.experimentertab.tasks.EvaluateInterleavedChunks
-
Defines the task's result type.
- getTaskResultType() - Method in class moa.gui.experimentertab.tasks.EvaluateInterleavedTestThenTrain
-
- getTaskResultType() - Method in class moa.gui.experimentertab.tasks.EvaluatePeriodicHeldOutTest
-
- getTaskResultType() - Method in class moa.gui.experimentertab.tasks.EvaluatePrequential
-
- getTaskResultType() - Method in class moa.gui.experimentertab.tasks.EvaluatePrequentialCV
-
- getTaskResultType() - Method in class moa.tasks.CacheShuffledStream
-
- getTaskResultType() - Method in class moa.tasks.EvaluateClustering
-
- getTaskResultType() - Method in class moa.tasks.EvaluateConceptDrift
-
- getTaskResultType() - Method in class moa.tasks.EvaluateInterleavedChunks
-
Defines the task's result type.
- getTaskResultType() - Method in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- getTaskResultType() - Method in class moa.tasks.EvaluateModel
-
- getTaskResultType() - Method in class moa.tasks.EvaluateModelMultiLabel
-
- getTaskResultType() - Method in class moa.tasks.EvaluateModelMultiTarget
-
- getTaskResultType() - Method in class moa.tasks.EvaluateModelRegression
-
- getTaskResultType() - Method in class moa.tasks.EvaluateMultipleClusterings
-
- getTaskResultType() - Method in class moa.tasks.EvaluateOnlineRecommender
-
- getTaskResultType() - Method in class moa.tasks.EvaluatePeriodicHeldOutTest
-
- getTaskResultType() - Method in class moa.tasks.EvaluatePrequential
-
- getTaskResultType() - Method in class moa.tasks.EvaluatePrequentialCV
-
- getTaskResultType() - Method in class moa.tasks.EvaluatePrequentialDelayed
-
- getTaskResultType() - Method in class moa.tasks.EvaluatePrequentialDelayedCV
-
- getTaskResultType() - Method in class moa.tasks.EvaluatePrequentialMultiLabel
-
- getTaskResultType() - Method in class moa.tasks.EvaluatePrequentialMultiTarget
-
- getTaskResultType() - Method in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- getTaskResultType() - Method in class moa.tasks.EvaluatePrequentialRegression
-
- getTaskResultType() - Method in class moa.tasks.FeatureImportanceConfig
-
- getTaskResultType() - Method in class moa.tasks.LearnModel
-
- getTaskResultType() - Method in class moa.tasks.LearnModelMultiLabel
-
- getTaskResultType() - Method in class moa.tasks.LearnModelMultiTarget
-
- getTaskResultType() - Method in class moa.tasks.LearnModelRegression
-
- getTaskResultType() - Method in class moa.tasks.MeasureStreamSpeed
-
- getTaskResultType() - Method in class moa.tasks.meta.ALMultiParamTask
-
- getTaskResultType() - Method in class moa.tasks.meta.ALPartitionEvaluationTask
-
- getTaskResultType() - Method in class moa.tasks.meta.ALPrequentialEvaluationTask
-
- getTaskResultType() - Method in class moa.tasks.Plot
-
Defines the task's result type.
- getTaskResultType() - Method in class moa.tasks.RunStreamTasks
-
- getTaskResultType() - Method in class moa.tasks.RunTasks
-
- getTaskResultType() - Method in interface moa.tasks.Task
-
Gets the result type of this task.
- getTaskResultType() - Method in class moa.tasks.WriteConfigurationToJupyterNotebook
-
- getTaskResultType() - Method in class moa.tasks.WriteMultipleStreamsToARFF
-
- getTaskResultType() - Method in class moa.tasks.WriteStreamToARFFFile
-
- getThreads() - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- getThreshold() - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Returns the threshold of the ClusteringFeature.
- getThreshold() - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Gets the threshold of this node.
- getTimePerObj() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getTimestamp() - Method in class moa.clusterers.clustree.Entry
-
Return the current timestamp.
- getTimestamp() - Method in class moa.clusterers.denstream.Timestamp
-
- getTimestamp() - Method in class moa.gui.visualization.DataPoint
-
- getTimestamp() - Method in class moa.streams.clustering.ClusterEvent
-
- getToolTipText() - Method in class moa.gui.visualization.PointPanel
-
- getToolTipText(MouseEvent) - Method in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Returns "<nominal value> [<nominal value count>]" if displaying
a bar plot and mouse is on some bar.
- getTopKFeatures(int, boolean) - Method in interface moa.learners.featureanalysis.FeatureImportanceClassifier
-
The output is a double array where values indicates the
original feature index and the order of the array its
ranking.
- getTopKFeatures(int, boolean) - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTree
-
- getTopKFeatures(int, boolean) - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTreeEnsemble
-
- getTotal() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getTotal() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- getTotal() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- getTotal() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- getTotal() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Reservoir
-
- getTotal() - Method in class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
-
- getTotalCount() - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- getTotalDelay() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- getTotalEntries() - Method in class moa.evaluation.MembershipMatrix
-
- getTotalWeightObserved() - Method in class moa.core.GaussianEstimator
-
- getTotalWeightObserved() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- getTotalWeightObserved() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- getTotalWeightObserved() - Method in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- getTotalWeightObserved() - Method in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- getTotalWeightObserved() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- getTotalWeightObserved() - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- getTotalWeightObserved() - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- getTotalWeightObserved() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- getTrainingPrediction() - Method in interface moa.classifiers.MultiTargetLearnerSemiSupervised
-
- getTrainingPrediction() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- getTrainingPrediction() - Method in interface moa.learners.LearnerSemiSupervised
-
- getTree() - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getTree() - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- getTreeLevel() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- getTreeRoot() - Method in class moa.classifiers.trees.HoeffdingTree
-
- getTreeRoot() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getType() - Method in class moa.streams.clustering.ClusterEvent
-
- getUpdateTime() - Method in class moa.clusterers.dstream.CharacteristicVector
-
- getUpperQuartile(int) - Method in class moa.evaluation.MeasureCollection
-
- getUserFeatures(int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- getUsers() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- getUsers() - Method in interface moa.recommender.rc.data.RecommenderData
-
- getValue() - Method in class com.github.javacliparser.AbstractClassOption
-
Returns the current object.
- getValue() - Method in class com.github.javacliparser.FloatOption
-
- getValue() - Method in class com.github.javacliparser.IntOption
-
- getValue() - Method in class com.github.javacliparser.StringOption
-
- getValue() - Method in class moa.classifiers.meta.DACC.Pair
-
- getValue() - Method in class moa.classifiers.rules.Predicates
-
- getValue() - Method in class moa.clusterers.meta.BooleanParameter
-
- getValue() - Method in class moa.clusterers.meta.CategoricalParameter
-
- getValue() - Method in class moa.clusterers.meta.IntegerParameter
-
- getValue() - Method in interface moa.clusterers.meta.IParameter
-
- getValue() - Method in class moa.clusterers.meta.NumericalParameter
-
- getValue() - Method in class moa.clusterers.meta.OrdinalParameter
-
- getValue() - Method in class moa.core.Measurement
-
- getValue() - Method in class moa.gui.experimentertab.Measure
-
- getValue(int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- getValue(int) - Method in class moa.core.DoubleVector
-
- getValue(int, int) - Method in class moa.evaluation.MeasureCollection
-
- getValueAsCLIString() - Method in class com.github.javacliparser.AbstractClassOption
-
- getValueAsCLIString() - Method in class com.github.javacliparser.ClassOption
-
- getValueAsCLIString() - Method in class com.github.javacliparser.FlagOption
-
- getValueAsCLIString() - Method in class com.github.javacliparser.FloatOption
-
- getValueAsCLIString() - Method in class com.github.javacliparser.IntOption
-
- getValueAsCLIString() - Method in class com.github.javacliparser.ListOption
-
- getValueAsCLIString() - Method in class com.github.javacliparser.MultiChoiceOption
-
- getValueAsCLIString() - Method in interface com.github.javacliparser.Option
-
Gets the value of a Command Line Interface text as a string
- getValueAsCLIString() - Method in class com.github.javacliparser.StringOption
-
- getValueAsCLIString() - Method in class moa.options.AbstractClassOption
-
- getValueAsCLIString() - Method in class moa.options.ClassOption
-
- getValueAsCLIString() - Method in class moa.options.ClassOptionWithNames
-
- getValueAsCLIString() - Method in class moa.options.WEKAClassOption
-
- getValueAt(int, int) - Method in class moa.gui.active.ALTaskManagerPanel.TaskTableModel
-
- getValueAt(int, int) - Method in class moa.gui.AuxiliarTaskManagerPanel.TaskTableModel
-
- getValueAt(int, int) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
-
- getValueAt(int, int) - Method in class moa.gui.experimentertab.TaskManagerTabPanel.TaskTableModel
-
- getValueAt(int, int) - Method in class moa.gui.LineGraphViewPanel.PlotTableModel
-
- getValueAt(int, int) - Method in class moa.gui.MultiLabelTaskManagerPanel.TaskTableModel
-
- getValueAt(int, int) - Method in class moa.gui.MultiTargetTaskManagerPanel.TaskTableModel
-
- getValueAt(int, int) - Method in class moa.gui.PreviewTableModel
-
- getValueAt(int, int) - Method in class moa.gui.RegressionTaskManagerPanel.TaskTableModel
-
- getValueAt(int, int) - Method in class moa.gui.TaskManagerPanel.TaskTableModel
-
- getValueCount() - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- getValueCount() - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- getValueCount() - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- getValueCount() - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- getValues() - Method in class moa.gui.experimentertab.Measure
-
- getValuesOfNominalAttributes(int, Instance) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getVariance() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getVariance() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- getVariance() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- getVariance() - Method in class moa.core.GaussianEstimator
-
- getVariances() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
Calculates the variance of this data set for each dimension
- getVarianceVector() - Method in class moa.clusterers.clustree.ClusKernel
-
- getVariedOption(OptionHandler, String) - Static method in class moa.options.DependentOptionsUpdater
-
Resolve the name of the varied parameter and return the corresponding option.
- getVariedParamName() - Method in class moa.evaluation.preview.PreviewCollection
-
- getVariedParamValues() - Method in class moa.evaluation.preview.PreviewCollection
-
- getVirtualChildren() - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- getVote() - Method in class moa.classifiers.rules.core.voting.Vote
-
- getVote() - Method in class moa.classifiers.rules.multilabel.core.voting.MultiLabelVote
-
- getVote(int, int) - Method in class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- getVote(int, int) - Method in interface com.yahoo.labs.samoa.instances.Prediction
-
The vote assigned to a class of an output attribute
- getVotes() - Method in class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- getVotes() - Method in interface com.yahoo.labs.samoa.instances.Prediction
-
The votes for the first output attribute
- getVotes(int) - Method in class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- getVotes(int) - Method in interface com.yahoo.labs.samoa.instances.Prediction
-
The votes for a given output attribute
- getVotes(Instance) - Method in class moa.classifiers.rules.AbstractAMRules
-
getVotes extension of the instance method getVotesForInstance
in moa.classifier.java
returns the prediction of the instance.
- getVotes(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
getVotes extension of the instance method getVotesForInstance
in moa.classifier.java
returns the prediction of the instance.
- getVotes(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
getVotes extension of the instance method getVotesForInstance
in moa.classifier.java
returns the prediction of the instance.
- getVotesForInstance(Instance) - Method in class moa.classifiers.AbstractClassifier
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.AbstractMultiLabelLearner
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.active.ALRandom
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.active.ALUncertainty
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.bayes.NaiveBayes
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
-
Calculates the class membership probabilities for the given test
instance.
- getVotesForInstance(Instance) - Method in interface moa.classifiers.Classifier
-
Predicts the class memberships for a given instance.
- getVotesForInstance(Instance) - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.functions.MajorityClass
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.functions.NoChange
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.functions.Perceptron
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.functions.SGD
-
Calculates the class membership probabilities for the given test
instance.
- getVotesForInstance(Instance) - Method in class moa.classifiers.functions.SGDMultiClass
-
Calculates the class membership probabilities for the given test
instance.
- getVotesForInstance(Instance) - Method in class moa.classifiers.functions.SPegasos
-
Calculates the class membership probabilities for the given test
instance.
- getVotesForInstance(Instance) - Method in class moa.classifiers.lazy.kNN
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.lazy.SAMkNN
-
Predicts the label of a given sample by using the STM, LTM and the CM.
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Predicts a class for an example.
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Predicts a class for an example.
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.AdaptiveRandomForest
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.ADOB
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.BOLE
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.DACC
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.DynamicWeightedMajority
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.imbalanced.CSMOTE
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.LearnNSE
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.LeveragingBag
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.LimAttClassifier
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OCBoost
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Predicts a class for an example.
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OnlineSmoothBoost
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OzaBag
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OzaBagAdwin
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OzaBagASHT
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OzaBoost
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.OzaBoostAdwin
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.PairedLearners
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.RandomRules
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.RCD
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.StreamingRandomPatches
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.meta.WEKAClassifier
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.multilabel.MEKAClassifier
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.multilabel.meta.OzaBagAdwinML
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.multilabel.meta.OzaBagML
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.oneclass.Autoencoder
-
Calculates the error between the autoencoder's reconstruction of the input and the argument instances.
- getVotesForInstance(Instance) - Method in class moa.classifiers.oneclass.HSTrees
-
Combine the anomaly scores from each HSTree in the forest and convert into a vote score.
- getVotesForInstance(Instance) - Method in class moa.classifiers.oneclass.NearestNeighbourDescription
-
Calculates the distance between the argument instance and its nearest neighbour as well as the distance between that
nearest neighbour and its own nearest neighbour.
- getVotesForInstance(Instance) - Method in class moa.classifiers.rules.AbstractAMRules
-
getVotesForInstance extension of the instance method getVotesForInstance
in moa.classifier.java
returns the prediction of the instance.
- getVotesForInstance(Instance) - Method in class moa.classifiers.rules.BinaryClassifierFromRegressor
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.rules.functions.AdaptiveNodePredictor
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.rules.functions.FadingTargetMean
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.rules.functions.LowPassFilteredLearner
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.rules.functions.Perceptron
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.rules.functions.TargetMean
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.rules.RuleClassifier
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.rules.RuleClassifierNBayes
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.trees.ARFFIMTDD
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.trees.DecisionStump
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.trees.EFDT
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.trees.FIMTDD
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.trees.HoeffdingTree
-
- getVotesForInstance(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- getVotesForInstance(Instance) - Method in interface moa.clusterers.Clusterer
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.ClusterGenerator
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.clustream.Clustream
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.clustream.WithKmeans
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.clustree.ClusTree
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.CobWeb
-
Classifies a given instance.
- getVotesForInstance(Instance) - Method in class moa.clusterers.denstream.WithDBSCAN
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.dstream.Dstream
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.kmeanspm.BICO
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.streamkm.StreamKM
-
- getVotesForInstance(Instance) - Method in class moa.clusterers.WekaClusteringAlgorithm
-
- getVotesForInstance(Instance) - Method in class moa.learners.ChangeDetectorLearner
-
- getVotesForInstance(Instance) - Method in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- getVotesForInstance(Instance) - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTree
-
- getVotesForInstance(Instance) - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTreeEnsemble
-
- getVotesForInstance(E) - Method in interface moa.learners.Learner
-
Predicts the class memberships for a given instance.
- getVotesForInstance(Example<Instance>) - Method in class moa.classifiers.AbstractClassifier
-
- getVotesForInstanceBinary(Instance) - Method in class moa.classifiers.meta.LeveragingBag
-
- getVotesForInstanceBinary(Instance) - Method in class moa.classifiers.meta.OzaBoostAdwin
-
- getVotesForInstancePerceptron(double[][], int[], int) - Method in class moa.classifiers.meta.LimAttClassifier
-
- getWaitWinFull() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- getWarning() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getWarningZone() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Gets whether the change detector is in the warning zone, after a warning
alert and before a change alert.
- getWarningZone() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector
-
Gets whether the change detector is in the warning zone, after a warning alert and before a change alert.
- getWeight() - Method in class moa.cluster.CFCluster
-
See interface Cluster
- getWeight() - Method in class moa.cluster.Cluster
-
Returns the weight of this cluster, not neccessarily normalized.
- getWeight() - Method in class moa.cluster.SphereCluster
-
- getWeight() - Method in class moa.clusterers.clustree.ClusKernel
-
- getWeight() - Method in class moa.clusterers.denstream.MicroCluster
-
- getWeight() - Method in class moa.clusterers.dstream.GridCluster
-
- getWeightedError() - Method in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
-
- getWeightedError() - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote
-
Returns the weighted error.
- getWeightedError() - Method in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- getWeightedError() - Method in interface moa.classifiers.rules.multilabel.core.voting.ErrorWeightedVoteMultiLabel
-
Returns the weighted error.
- getWeights() - Method in class moa.classifiers.functions.Perceptron
-
- getWeights() - Method in class moa.classifiers.rules.core.voting.AbstractErrorWeightedVote
-
- getWeights() - Method in interface moa.classifiers.rules.core.voting.ErrorWeightedVote
-
Return the weights error.
- getWeights() - Method in class moa.classifiers.rules.functions.Perceptron
-
- getWeights() - Method in class moa.classifiers.rules.multilabel.core.voting.AbstractErrorWeightedVoteMultiLabel
-
- getWeights() - Method in interface moa.classifiers.rules.multilabel.core.voting.ErrorWeightedVoteMultiLabel
-
Return the weights error.
- getWeights() - Method in class moa.classifiers.trees.ARFFIMTDD.FIMTDDPerceptron
-
- getWeights() - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
-
- getWeightSeen() - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- getWeightSeen() - Method in class moa.classifiers.rules.RuleClassifier
-
- getWeightSeen() - Method in class moa.classifiers.trees.EFDT.ActiveLearningNode
-
- getWeightSeen() - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
-
- getWeightSeen() - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
-
- getWeightSeenAtLastSplitEvaluation() - Method in class moa.classifiers.trees.EFDT.ActiveLearningNode
-
- getWeightSeenAtLastSplitEvaluation() - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
-
- getWeightSeenAtLastSplitEvaluation() - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
-
- getWeightSeenSinceExpansion() - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- getWeightSeenSinceExpansion() - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- getWidth() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getWidth() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- getWidth() - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector.SeqDrift1
-
- getWidth() - Method in class moa.gui.experimentertab.ImageChart
-
Return the width.
- getWidthT() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- getWindowSize() - Method in class moa.gui.featureanalysis.FeatureImportancePanel
-
- getWindowSize() - Method in class moa.tasks.FeatureImportanceConfig
-
- getWorkbenchInfoString() - Static method in class moa.core.Globals
-
- getWorstError() - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- getWVDIndexes() - Method in class moa.classifiers.meta.DACC
-
Returns the classifiers that vote for the final prediction
when the WVD combination function is selected
- getYoungestEntry() - Method in class moa.core.FixedLengthList
-
- GIF - moa.gui.experimentertab.PlotTab.Terminal
-
- GIF - moa.tasks.Plot.Terminal
-
- GiniSplitCriterion - Class in moa.classifiers.core.splitcriteria
-
Class for computing splitting criteria using Gini
with respect to distributions of class values.
- GiniSplitCriterion() - Constructor for class moa.classifiers.core.splitcriteria.GiniSplitCriterion
-
- globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance
-
Returns a string describing this object.
- globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KMeansInpiredMethod
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MedianOfWidestDimension
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MidPointOfWidestDimension
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Returns a string describing this nearest neighbour search algorithm.
- globalInfo() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Returns a string describing this object.
- globalInfo() - Method in class weka.classifiers.meta.MOA
-
Returns a string describing the classifier.
- globalInfo() - Method in class weka.datagenerators.classifiers.classification.MOA
-
Returns a string describing this data generator.
- Globals - Class in moa.core
-
Class for storing global information about current version of MOA.
- Globals() - Constructor for class moa.core.Globals
-
- gnuplotPathOption - Variable in class moa.tasks.Plot
-
Path to gunplot's binary directory, for example C:\Tools\Gnuplot\binary.
- gr(double, double) - Static method in class moa.core.Utils
-
Tests if a is greater than b.
- gracePeriodOption - Variable in class moa.classifiers.multilabel.trees.ISOUPTree
-
- gracePeriodOption - Variable in class moa.classifiers.rules.AbstractAMRules
-
- gracePeriodOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- gracePeriodOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- gracePeriodOption - Variable in class moa.classifiers.rules.RuleClassifier
-
- gracePeriodOption - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- gracePeriodOption - Variable in class moa.classifiers.trees.DecisionStump
-
- gracePeriodOption - Variable in class moa.classifiers.trees.EFDT
-
- gracePeriodOption - Variable in class moa.classifiers.trees.FIMTDD
-
- gracePeriodOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- gracePeriodOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- gracePeriodOption - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- gracePerionOption - Variable in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- GradualChangeGenerator - Class in moa.streams.generators.cd
-
- GradualChangeGenerator() - Constructor for class moa.streams.generators.cd.GradualChangeGenerator
-
- graph() - Method in class moa.clusterers.CobWeb
-
Generates the graph string of the Cobweb tree
- GraphAxes - Class in moa.gui.visualization
-
- GraphAxes() - Constructor for class moa.gui.visualization.GraphAxes
-
Creates new form GraphAxes
- GraphCanvas - Class in moa.gui.visualization
-
- GraphCanvas() - Constructor for class moa.gui.visualization.GraphCanvas
-
Creates new form GraphCanvas
- GraphCurve - Class in moa.gui.visualization
-
- GraphCurve() - Constructor for class moa.gui.visualization.GraphCurve
-
Creates new form GraphCurve
- GraphMultiCurve - Class in moa.gui.visualization
-
GraphMultiCurve is an an implementation of AbstractGraphPlot that draws
several curves on a Canvas.
- GraphMultiCurve() - Constructor for class moa.gui.visualization.GraphMultiCurve
-
- GraphScatter - Class in moa.gui.visualization
-
GraphScatter is an implementation of AbstractGraphPlot that draws a scatter
plot.
- GraphScatter() - Constructor for class moa.gui.visualization.GraphScatter
-
- greaterThan - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
-
- GreenwaldKhannaNumericAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers
-
Class for observing the class data distribution for a numeric attribute using Greenwald and Khanna methodology.
- GreenwaldKhannaNumericAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
-
- GreenwaldKhannaQuantileSummary - Class in moa.core
-
Class for representing summaries of Greenwald and Khanna quantiles.
- GreenwaldKhannaQuantileSummary(int) - Constructor for class moa.core.GreenwaldKhannaQuantileSummary
-
- GreenwaldKhannaQuantileSummary.Tuple - Class in moa.core
-
- gridBagConstraints - Variable in class moa.gui.experimentertab.TaskTextViewerPanel
-
- gridBagConstraints - Variable in class moa.gui.TaskTextViewerPanel
-
- GridCluster - Class in moa.clusterers.dstream
-
Grid Clusters are defined in Definition 3.6 of Chen and Tu 2007 as:
Let G =(g1, ·· · ,gm) be a grid group, if every inside grid of G is
a dense grid and every outside grid is either a dense grid or a
transitional grid, then G is a grid cluster.
- GridCluster(CFCluster, List<CFCluster>, int) - Constructor for class moa.clusterers.dstream.GridCluster
-
- GridCluster(CFCluster, List<CFCluster>, HashMap<DensityGrid, Boolean>, int) - Constructor for class moa.clusterers.dstream.GridCluster
-
- grOrEq(double, double) - Static method in class moa.core.Utils
-
Tests if a is greater or equal to b.
- growthAllowed - Variable in class moa.classifiers.trees.EFDT
-
- growthAllowed - Variable in class moa.classifiers.trees.HoeffdingTree
-
- GUI - Class in moa.gui
-
The main class for the MOA gui.
- GUI() - Constructor for class moa.gui.GUI
-
- GUIDefaults - Class in moa.gui
-
This class offers get methods for the default GUI settings in
the props file moa/gui/GUI.props.
- GUIDefaults() - Constructor for class moa.gui.GUIDefaults
-
- GUIUtils - Class in moa.gui
-
This class offers util methods for displaying dialogs showing errors or exceptions.
- GUIUtils() - Constructor for class moa.gui.GUIUtils
-
- i - Variable in class moa.classifiers.meta.PairedLearners
-
- i - Variable in class moa.gui.experimentertab.statisticaltests.Relation
-
- Iadem2 - Class in moa.classifiers.trees.iadem
-
- Iadem2() - Constructor for class moa.classifiers.trees.iadem.Iadem2
-
- Iadem2.LeafNode - Class in moa.classifiers.trees.iadem
-
- Iadem2.LeafNodeNB - Class in moa.classifiers.trees.iadem
-
- Iadem2.LeafNodeNBKirkby - Class in moa.classifiers.trees.iadem
-
- Iadem2.LeafNodeWeightedVote - Class in moa.classifiers.trees.iadem
-
- Iadem2.Node - Class in moa.classifiers.trees.iadem
-
- Iadem2.NominalVirtualNode - Class in moa.classifiers.trees.iadem
-
- Iadem2.NumericVirtualNode - Class in moa.classifiers.trees.iadem
-
- Iadem2.SplitNode - Class in moa.classifiers.trees.iadem
-
- Iadem2.VirtualNode - Class in moa.classifiers.trees.iadem
-
- Iadem3 - Class in moa.classifiers.trees.iadem
-
- Iadem3() - Constructor for class moa.classifiers.trees.iadem.Iadem3
-
- Iadem3.AdaptiveLeafNode - Class in moa.classifiers.trees.iadem
-
- Iadem3.AdaptiveLeafNodeNB - Class in moa.classifiers.trees.iadem
-
- Iadem3.AdaptiveLeafNodeNBAdaptive - Class in moa.classifiers.trees.iadem
-
- Iadem3.AdaptiveLeafNodeNBKirkby - Class in moa.classifiers.trees.iadem
-
- Iadem3.AdaptiveLeafNodeWeightedVote - Class in moa.classifiers.trees.iadem
-
- Iadem3.AdaptiveNominalVirtualNode - Class in moa.classifiers.trees.iadem
-
- Iadem3.AdaptiveNumericVirtualNode - Class in moa.classifiers.trees.iadem
-
- Iadem3.AdaptiveSplitNode - Class in moa.classifiers.trees.iadem
-
- Iadem3.restartsVariablesAtDrift - Interface in moa.classifiers.trees.iadem
-
- Iadem3Subtree - Class in moa.classifiers.trees.iadem
-
- Iadem3Subtree(Iadem2.Node, int, Iadem3, Instance) - Constructor for class moa.classifiers.trees.iadem.Iadem3Subtree
-
- IademAttributeSplitSuggestion - Class in moa.classifiers.trees.iadem
-
- IademAttributeSplitSuggestion(InstanceConditionalTest, double[][], double, double) - Constructor for class moa.classifiers.trees.iadem.IademAttributeSplitSuggestion
-
- IademCommonProcedures - Class in moa.classifiers.trees.iadem
-
- IademCommonProcedures(double) - Constructor for class moa.classifiers.trees.iadem.IademCommonProcedures
-
- IademException - Exception in moa.classifiers.trees.iadem
-
- IademException(String, String, String) - Constructor for exception moa.classifiers.trees.iadem.IademException
-
- IademGaussianNumericAttributeClassObserver - Class in moa.classifiers.trees.iadem
-
- IademGaussianNumericAttributeClassObserver() - Constructor for class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- IademGaussianNumericAttributeClassObserver(int) - Constructor for class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- IademGreenwaldKhannaNumericAttributeClassObserver - Class in moa.classifiers.trees.iadem
-
- IademGreenwaldKhannaNumericAttributeClassObserver() - Constructor for class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- IademGreenwaldKhannaNumericAttributeClassObserver(int) - Constructor for class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- IademGreenwaldKhannaQuantileSummary - Class in moa.classifiers.trees.iadem
-
- IademGreenwaldKhannaQuantileSummary(int) - Constructor for class moa.classifiers.trees.iadem.IademGreenwaldKhannaQuantileSummary
-
- IademNominalAttributeBinaryTest - Class in moa.classifiers.trees.iadem
-
- IademNominalAttributeBinaryTest(int, int) - Constructor for class moa.classifiers.trees.iadem.IademNominalAttributeBinaryTest
-
- IademNominalAttributeMultiwayTest - Class in moa.classifiers.trees.iadem
-
- IademNominalAttributeMultiwayTest(int, int) - Constructor for class moa.classifiers.trees.iadem.IademNominalAttributeMultiwayTest
-
- IademNumericAttributeBinaryTest - Class in moa.classifiers.trees.iadem
-
- IademNumericAttributeBinaryTest(int, double, boolean) - Constructor for class moa.classifiers.trees.iadem.IademNumericAttributeBinaryTest
-
- IademNumericAttributeObserver - Interface in moa.classifiers.trees.iadem
-
- IademSplitCriterion - Class in moa.classifiers.trees.iadem
-
- IademSplitCriterion() - Constructor for class moa.classifiers.trees.iadem.IademSplitCriterion
-
- IademSplitCriterion(String) - Constructor for class moa.classifiers.trees.iadem.IademSplitCriterion
-
- IademVFMLNumericAttributeClassObserver - Class in moa.classifiers.trees.iadem
-
- IademVFMLNumericAttributeClassObserver() - Constructor for class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- IademVFMLNumericAttributeClassObserver(int) - Constructor for class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- IademVFMLNumericAttributeClassObserver.Bin - Class in moa.classifiers.trees.iadem
-
- ICVarianceReduction - Class in moa.classifiers.multilabel.core.splitcriteria
-
- ICVarianceReduction() - Constructor for class moa.classifiers.multilabel.core.splitcriteria.ICVarianceReduction
-
- id - Variable in class moa.classifiers.rules.core.Rule.Builder
-
- id - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
-
- id - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
-
- id - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- id - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector.Outlier
-
- id - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- id(int) - Method in class moa.classifiers.rules.core.Rule.Builder
-
- ID - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- ID - Variable in class moa.classifiers.trees.ARFFIMTDD.Node
-
- ID - Variable in class moa.classifiers.trees.FIMTDD.Node
-
- ID - Static variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel.PreprocessDefaults
-
- IDenseMacroCluster - Interface in moa.clusterers.macro
-
- illegalNameCharacters - Static variable in class com.github.javacliparser.AbstractOption
-
Array of characters not valid to use in option names.
- IMacroClusterer - Interface in moa.clusterers.macro
-
- image - Variable in class moa.gui.experimentertab.RankingGraph
-
- ImageChart - Class in moa.gui.experimentertab
-
This class allows to handle the properties of the graph created by
JFreeChart.
- ImageChart() - Constructor for class moa.gui.experimentertab.ImageChart
-
Default constructor.
- ImageChart(String, JFreeChart) - Constructor for class moa.gui.experimentertab.ImageChart
-
Constructor.
- ImageChart(String, JFreeChart, int, int) - Constructor for class moa.gui.experimentertab.ImageChart
-
Constructor.
- ImagePanel - Class in moa.gui.experimentertab
-
This class creates a panel with an image.
- ImagePanel(JFreeChart) - Constructor for class moa.gui.experimentertab.ImagePanel
-
Class Constructor.
- ImageTreePanel - Class in moa.gui.experimentertab
-
This class creates a JTree panel to show the images generated with
JFreeChart.
- ImageTreePanel(ImageChart[]) - Constructor for class moa.gui.experimentertab.ImageTreePanel
-
Constructor.
- ImageViewer - Class in moa.gui.experimentertab
-
This class creates a window where images generated with JFreeChart are
displayed.
- ImageViewer(ImageTreePanel, String) - Constructor for class moa.gui.experimentertab.ImageViewer
-
Class constructor.
- iMaxMemUsage - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- ImbalancedStream - Class in moa.streams
-
Imbalanced Stream.
- ImbalancedStream() - Constructor for class moa.streams.ImbalancedStream
-
- imgPath - Variable in class moa.gui.experimentertab.RankingGraph
-
- ImmutableCapabilities - Class in moa.capabilities
-
Set of capabilities that cannot be modified after creation.
- ImmutableCapabilities(Capability...) - Constructor for class moa.capabilities.ImmutableCapabilities
-
Creates an immutable set of capabilities.
- implementsMicroClusterer() - Method in class moa.clusterers.AbstractClusterer
-
- implementsMicroClusterer() - Method in interface moa.clusterers.Clusterer
-
- implementsMicroClusterer() - Method in class moa.clusterers.ClusterGenerator
-
- implementsMicroClusterer() - Method in class moa.clusterers.clustream.Clustream
-
- implementsMicroClusterer() - Method in class moa.clusterers.clustream.WithKmeans
-
Miscellaneous
- implementsMicroClusterer() - Method in class moa.clusterers.clustree.ClusTree
-
- implementsMicroClusterer() - Method in class moa.clusterers.denstream.WithDBSCAN
-
- implementsMicroClusterer() - Method in class moa.clusterers.kmeanspm.BICO
-
- implementsMicroClusterer() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- improveObjectOnce(int) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- IMPULSES - moa.gui.experimentertab.PlotTab.PlotStyle
-
- IMPULSES - moa.tasks.Plot.PlotStyle
-
- inactiveLeafByteSizeEstimate - Variable in class moa.classifiers.trees.EFDT
-
- inactiveLeafByteSizeEstimate - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- inactiveLeafByteSizeEstimate - Variable in class moa.classifiers.trees.HoeffdingTree
-
- inactiveLeafNodeCount - Variable in class moa.classifiers.trees.EFDT
-
- inactiveLeafNodeCount - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- inactiveLeafNodeCount - Variable in class moa.classifiers.trees.HoeffdingTree
-
- InactiveLearningNode(double[]) - Constructor for class moa.classifiers.trees.EFDT.InactiveLearningNode
-
- InactiveLearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.InactiveLearningNode
-
- InactiveLearningNode(double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.InactiveLearningNode
-
- incompleteBeta(double, double, double) - Static method in class moa.core.Statistics
-
Returns the Incomplete Beta Function evaluated from zero to xx.
- incompleteBetaFraction1(double, double, double) - Static method in class moa.core.Statistics
-
Continued fraction expansion #1 for incomplete beta integral.
- incompleteBetaFraction2(double, double, double) - Static method in class moa.core.Statistics
-
Continued fraction expansion #2 for incomplete beta integral.
- incompleteGamma(double, double) - Static method in class moa.core.Statistics
-
Returns the Incomplete Gamma function.
- incompleteGammaComplement(double, double) - Static method in class moa.core.Statistics
-
Returns the Complemented Incomplete Gamma function.
- incrCutPoint - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- increase() - Method in class moa.clusterers.denstream.Timestamp
-
- incrementValueOption - Variable in class moa.tasks.RunStreamTasks
-
- incrementValueOption - Variable in class moa.tasks.RunTasks
-
- incrNumberOfInstancesProcessed() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- independentBoundedConditionSum - Variable in class moa.classifiers.core.driftdetection.HDDM_W_Test.SampleInfo
-
- index - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeapElement
-
the index of this element.
- index - Variable in class moa.classifiers.meta.ADACC
-
Current stability index
- index - Variable in class moa.classifiers.meta.LearnNSE
-
- index - Variable in class moa.classifiers.meta.RCD
-
- index(int) - Method in class com.yahoo.labs.samoa.instances.DenseInstanceData
-
Index.
- index(int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Gets the index of the attribute given the index of the array in a sparse
representation.
- index(int) - Method in interface com.yahoo.labs.samoa.instances.InstanceData
-
Index.
- index(int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Index.
- index(int) - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Index.
- indexOf(Attribute) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Returns the index of an Attribute.
- indexOfAttribute(Attribute) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Index of an Attribute.
- indexOfAttribute(Attribute) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- indexOfValue(String) - Method in class com.yahoo.labs.samoa.instances.Attribute
-
Index of value.
- indexOriginal - Variable in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- indexOriginal - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- indexOriginal - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- indexValues - Variable in class com.yahoo.labs.samoa.instances.AttributesInformation
-
- indexValues - Variable in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
The index values.
- indexValues - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- indexValues - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- indice - Variable in class moa.gui.experimentertab.statisticaltests.Pareja
-
- indicesIrrelevants - Variable in class com.yahoo.labs.samoa.instances.Instances
-
Indices of irrelevant features.
- indicesRelevants - Variable in class com.yahoo.labs.samoa.instances.Instances
-
Indices of relevant features.
- info(int[]) - Static method in class moa.core.Utils
-
Computes entropy for an array of integers.
- InfoGainSplitCriterion - Class in moa.classifiers.core.splitcriteria
-
Class for computing splitting criteria using information gain
with respect to distributions of class values.
- InfoGainSplitCriterion() - Constructor for class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
-
- InfoGainSplitCriterionMultilabel - Class in moa.classifiers.core.splitcriteria
-
Class for computing splitting criteria using information gain with respect to
distributions of class values for Multilabel data.
- InfoGainSplitCriterionMultilabel() - Constructor for class moa.classifiers.core.splitcriteria.InfoGainSplitCriterionMultilabel
-
- InfoPanel - Class in moa.gui.visualization
-
- InfoPanel(JFrame) - Constructor for class moa.gui.visualization.InfoPanel
-
Creates new form InfoPanel
- init() - Method in class moa.classifiers.lazy.SAMkNN
-
- init() - Method in class moa.classifiers.multitarget.BasicMultiLabelLearner
-
- init() - Method in class moa.classifiers.multitarget.BasicMultiTargetRegressor
-
- init() - Method in class moa.classifiers.rules.multilabel.functions.MultiLabelNaiveBayes
-
- init() - Method in class moa.classifiers.rules.multilabel.functions.MultiLabelPerceptronClassification
-
- init() - Method in class moa.classifiers.rules.multilabel.functions.MultiTargetMeanRegressor
-
- init() - Method in class moa.classifiers.rules.multilabel.functions.MultiTargetPerceptronRegressor
-
- init() - Method in class moa.clusterers.meta.Algorithm
-
- init() - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- init() - Method in class moa.recommender.dataset.impl.FlixsterDataset
-
- init() - Method in class moa.recommender.dataset.impl.JesterDataset
-
- init() - Method in class moa.recommender.dataset.impl.MovielensDataset
-
- Init() - Method in class moa.clusterers.outliers.AbstractC.AbstractC
-
- Init() - Method in class moa.clusterers.outliers.Angiulli.ApproxSTORM
-
- Init() - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM
-
- Init() - Method in class moa.clusterers.outliers.AnyOut.AnyOut
-
- Init() - Method in class moa.clusterers.outliers.MCOD.MCOD
-
- Init() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- Init() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCOD
-
- initCache() - Static method in class moa.core.AutoClassDiscovery
-
Initializes the class cache
- initClassifiers - Variable in class moa.classifiers.meta.LimAttClassifier
-
- initEnsemble(Instance) - Method in class moa.classifiers.meta.AdaptiveRandomForest
-
- initEnsemble(Instance) - Method in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- initEnsemble(Instance) - Method in class moa.classifiers.meta.StreamingRandomPatches
-
- initHeader(Instances) - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
-
- INITIAL_DIR - Static variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel.PreprocessDefaults
-
- INITIAL_DIR_KEY - Static variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel.PreprocessDefaults
-
- initialDBScan() - Method in class moa.clusterers.denstream.WithDBSCAN
-
- initialisePerceptron - Variable in class moa.classifiers.rules.functions.Perceptron
-
- initialize() - Method in class moa.classifiers.core.driftdetection.RDDM
-
- initialize() - Method in class moa.classifiers.core.driftdetection.STEPD
-
- initialize() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
initializes the ranges and the attributes being used.
- initialize(Collection<Instance>) - Method in class moa.classifiers.oneclass.Autoencoder
-
Initializes the Autoencoder classifier on the argument trainingPoints.
- initialize(Collection<Instance>) - Method in class moa.classifiers.oneclass.HSTrees
-
Initializes the Streaming HS-Trees classifier on the argument trainingPoints.
- initialize(Collection<Instance>) - Method in class moa.classifiers.oneclass.NearestNeighbourDescription
-
Initializes the Nearest Neighbour Distance (NN-d) classifier with the argument training points.
- initialize(Collection<Instance>) - Method in interface moa.classifiers.OneClassClassifier
-
Allows a one class classifier to be initialized with a starting set of training instances.
- initialize(RuleActiveLearningNode) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- initialize(RuleActiveLearningNode) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- initializeAlternateTree() - Method in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- initializeAlternateTree() - Method in class moa.classifiers.trees.FIMTDD.InnerNode
-
- initializeAlternateTree(ISOUPTree) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- initializeAttibutesMask(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- initializeAttributeIndices() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
initializes the attribute indices.
- initialized - Variable in class moa.clusterers.streamkm.StreamKM
-
- initializeEntry(Entry, long) - Method in class moa.clusterers.clustree.Entry
-
When this entry is empty, give it it's first values.
- initializeRanges() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Initializes the ranges using all instances of the dataset.
- initializeRanges(int[]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Initializes the ranges of a subset of the instances of this dataset.
- initializeRanges(int[], int, int) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Initializes the ranges of a subset of the instances of this dataset.
- initializeRangesEmpty(int, double[][]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Used to initialize the ranges.
- initializeRuleStatistics(RuleClassification, Predicates, Instance) - Method in class moa.classifiers.rules.RuleClassifier
-
- initializeWeights() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.MultitargetPerceptron
-
- initialNumInstancesOption - Variable in class moa.classifiers.meta.LimAttClassifier
-
- initialPauseInterval - Static variable in class moa.gui.visualization.RunOutlierVisualizer
-
the pause interval, being read from the gui at startup
- initialPauseInterval - Static variable in class moa.gui.visualization.RunVisualizer
-
the pause interval, being read from the gui at startup
- initialString - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- initialWindowSizeOption - Variable in class moa.tasks.EvaluatePrequentialDelayed
-
- initKernels() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- initKm1 - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- initMatrixCodes - Variable in class moa.classifiers.meta.LeveragingBag
-
- initMatrixCodes - Variable in class moa.classifiers.meta.LimAttClassifier
-
- initMatrixCodes - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- InitNode() - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- initObject(int, double[]) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- initPointsOption - Variable in class moa.clusterers.denstream.WithDBSCAN
-
- initVariables() - Method in class moa.classifiers.meta.ADACC
-
- initVariables() - Method in class moa.classifiers.meta.DACC
-
Initializes the method variables
- initVisualEvalPanel() - Method in class moa.gui.experimentertab.TaskTextViewerPanel
-
- initVisualEvalPanel() - Method in class moa.gui.TaskTextViewerPanel
-
- INLIER_MC - moa.clusterers.outliers.MCOD.ISBIndex.ISBNode.NodeType
-
- INLIER_PD - moa.clusterers.outliers.MCOD.ISBIndex.ISBNode.NodeType
-
- INMEM_PREFIX_STRING - Static variable in class com.github.javacliparser.AbstractClassOption
-
The prefix text to use to indicate inmem.
- INMEM_PREFIX_STRING - Static variable in class moa.options.AbstractClassOption
-
The prefix text to use to indicate inmem.
- InnerNode(ISOUPTree) - Constructor for class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- InnerNode(ARFFIMTDD) - Constructor for class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- InnerNode(FIMTDD) - Constructor for class moa.classifiers.trees.FIMTDD.InnerNode
-
- input(boolean) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- input(double) - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Adding a numeric value to the change detector
The output of the change detector is modified after the insertion of a
new item inside.
- input(double) - Method in class moa.classifiers.core.driftdetection.ADWINChangeDetector
-
- input(double) - Method in interface moa.classifiers.core.driftdetection.ChangeDetector
-
Adding a numeric value to the change detector
The output of the change detector is modified after the insertion of a
new item inside.
- input(double) - Method in class moa.classifiers.core.driftdetection.CusumDM
-
- input(double) - Method in class moa.classifiers.core.driftdetection.DDM
-
- input(double) - Method in class moa.classifiers.core.driftdetection.EDDM
-
- input(double) - Method in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
-
- input(double) - Method in class moa.classifiers.core.driftdetection.EWMAChartDM
-
- input(double) - Method in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
-
- input(double) - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- input(double) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- input(double) - Method in class moa.classifiers.core.driftdetection.PageHinkleyDM
-
- input(double) - Method in class moa.classifiers.core.driftdetection.RDDM
-
- input(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector
-
- input(double) - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
-
- input(double) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
-
- input(double) - Method in class moa.classifiers.core.driftdetection.STEPD
-
- input(double) - Method in class moa.classifiers.rules.core.changedetection.NoChangeDetection
-
- inputAttribute(int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Gets an input attribute given its index.
- inputAttribute(int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- inputAttribute(int) - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- inputAttribute(int) - Method in class com.yahoo.labs.samoa.instances.InstancesHeader
-
- inputAttributeIndex(int) - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- InputAttributesSelector - Interface in moa.classifiers.rules.multilabel.inputselectors
-
- inputByteSize - Variable in class moa.core.InputStreamProgressMonitor
-
The number of bytes to read in total
- inputBytesRead - Variable in class moa.core.InputStreamProgressMonitor
-
The number of bytes read so far
- inputFilesOption - Variable in class moa.tasks.Plot
-
Comma separated list of input *csv files.
- inputInstance - Variable in class moa.streams.ConceptDriftRealStream
-
- inputSelector - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- inputSelectorOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- inputSelectorOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- inputsSelected - Variable in class moa.streams.filters.SelectAttributesFilter
-
- inputsToLearn - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- inputStream - Variable in class moa.streams.ConceptDriftRealStream
-
- inputStream - Variable in class moa.streams.ConceptDriftStream
-
- inputStream - Variable in class moa.streams.filters.AbstractMultiLabelStreamFilter
-
The input stream to this filter.
- inputStream - Variable in class moa.streams.filters.AbstractStreamFilter
-
The input stream to this filter.
- InputStreamProgressMonitor - Class in moa.core
-
Class for monitoring the progress of reading an input stream.
- InputStreamProgressMonitor(InputStream) - Constructor for class moa.core.InputStreamProgressMonitor
-
- inputStringOption - Variable in class moa.streams.filters.SelectAttributesFilter
-
- inputValues - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- inRanges(Instance, double[][]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Test if an instance is within the given ranges.
- insert(double) - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- insert(Instance, long) - Method in class moa.clusterers.clustream.ClustreamKernel
-
- insert(Instance, long) - Method in class moa.clusterers.denstream.MicroCluster
-
- insert(CFCluster) - Method in class moa.clusterers.macro.NonConvexCluster
-
- insert(ClusKernel, Budget, long) - Method in class moa.clusterers.clustree.ClusTree
-
Insert a new point in the Tree.
- Insert(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.AbstractC.ISBIndex
-
- Insert(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.Angiulli.ISBIndex
-
- Insert(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.ISBIndex
-
- Insert(ISBIndex.ISBNode, Long) - Method in class moa.clusterers.outliers.MCOD.MCODBase.EventQueue
-
- Insert(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex
-
- Insert(ISBIndex.ISBNode, Long) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventQueue
-
- insertAttributeAt(int) - Method in class com.yahoo.labs.samoa.instances.DenseInstanceData
-
- insertAttributeAt(int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Insert attribute at.
- insertAttributeAt(int) - Method in interface com.yahoo.labs.samoa.instances.InstanceData
-
Inserts an attribute.
- insertAttributeAt(int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Insert attribute at.
- insertAttributeAt(int) - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
- insertAttributeAt(Attribute, int) - Method in class com.yahoo.labs.samoa.instances.AttributesInformation
-
- insertAttributeAt(Attribute, int) - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- insertAttributeAt(Attribute, int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Insert attribute at.
- insertEntry(LearningEvaluation) - Method in class moa.evaluation.preview.LearningCurve
-
- insertLotsHoles(ArrayList<Double>, ArrayList<Integer>, double, double) - Static method in class moa.classifiers.trees.iadem.IademCommonProcedures
-
- insertSorted(double, Instance) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
Inserts an instance neighbor into the list, maintaining the list
sorted by distance.
- insertTuple(GreenwaldKhannaQuantileSummary.Tuple, int) - Method in class moa.core.GreenwaldKhannaQuantileSummary
-
- insertValue(double, double) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
-
- insertValue(double, double, double) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
-
Insert a new value into the tree, updating both the sum of values and
sum of squared values arrays
- insertValue(double, double, double) - Method in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver.Node
-
Insert a new value into the tree, updating both the sum of values and
sum of squared values arrays
- insertValue(double, int, double) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
-
- inst - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
-
- inst - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
-
- inst - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- inst - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector.Outlier
-
- inst - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- install() - Static method in class moa.gui.LookAndFeel
-
Installs the look and feel.
- installJavaLookAndFeel(String) - Static method in class moa.gui.LookAndFeel
-
Attempts to install the specified Java Look'n'Feel.
- installJideLookAndFeel(int) - Static method in class moa.gui.LookAndFeel
-
Attempts to install the specified JIDE style.
- instance - Variable in class moa.classifiers.rules.RuleClassifier
-
- instance - Variable in class moa.core.InstanceExample
-
- instance(int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Instance.
- Instance - Interface in com.yahoo.labs.samoa.instances
-
The Interface Instance.
- InstanceAttributesSelector - Class in moa.classifiers.rules.multilabel.instancetransformers
-
Transforms instances considering both a subset of input attributes
and a subset of output attributes
- InstanceAttributesSelector(InstancesHeader, int[], int[]) - Constructor for class moa.classifiers.rules.multilabel.instancetransformers.InstanceAttributesSelector
-
- instanceChildIndex(Instance) - Method in class moa.classifiers.trees.ARFFIMTDD.SplitNode
-
- instanceChildIndex(Instance) - Method in class moa.classifiers.trees.EFDT.SplitNode
-
- instanceChildIndex(Instance) - Method in class moa.classifiers.trees.FIMTDD.SplitNode
-
- instanceChildIndex(Instance) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- instanceChildIndex(Instance) - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- instanceChildIndex(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- instanceChildIndex(MultiLabelInstance) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.SplitNode
-
- InstanceConditionalBinaryTest - Class in moa.classifiers.core.conditionaltests
-
Abstract binary conditional test for instances to use to split nodes in Hoeffding trees.
- InstanceConditionalBinaryTest() - Constructor for class moa.classifiers.core.conditionaltests.InstanceConditionalBinaryTest
-
- InstanceConditionalTest - Class in moa.classifiers.core.conditionaltests
-
Abstract conditional test for instances to use to split nodes in Hoeffding trees.
- InstanceConditionalTest() - Constructor for class moa.classifiers.core.conditionaltests.InstanceConditionalTest
-
- instanceConverter - Variable in class moa.classifiers.meta.WEKAClassifier
-
- instanceConverter - Variable in class moa.classifiers.multilabel.MEKAClassifier
-
- instanceConverter - Variable in class moa.clusterers.WekaClusteringAlgorithm
-
- instanceConverter - Variable in class weka.classifiers.meta.MOA
-
- instanceConverter - Variable in class weka.datagenerators.classifiers.classification.MOA
-
- instanceData - Variable in class com.yahoo.labs.samoa.instances.InstanceImpl
-
The instance data.
- InstanceData - Interface in com.yahoo.labs.samoa.instances
-
The Interface InstanceData.
- InstanceExample - Class in moa.core
-
- InstanceExample(Instance) - Constructor for class moa.core.InstanceExample
-
- instanceGenerated - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- instanceGenerated - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- instanceHeader - Variable in class com.yahoo.labs.samoa.instances.InstanceImpl
-
The instance information.
- instanceHeader - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- InstanceImpl - Class in com.yahoo.labs.samoa.instances
-
The Class InstanceImpl.
- InstanceImpl(double, double[]) - Constructor for class com.yahoo.labs.samoa.instances.InstanceImpl
-
Instantiates a new instance.
- InstanceImpl(double, double[], int[], int) - Constructor for class com.yahoo.labs.samoa.instances.InstanceImpl
-
Instantiates a new instance.
- InstanceImpl(double, InstanceData) - Constructor for class com.yahoo.labs.samoa.instances.InstanceImpl
-
Instantiates a new instance.
- InstanceImpl(int) - Constructor for class com.yahoo.labs.samoa.instances.InstanceImpl
-
Instantiates a new instance.
- InstanceImpl(InstanceImpl) - Constructor for class com.yahoo.labs.samoa.instances.InstanceImpl
-
Instantiates a new instance.
- instanceInformation - Variable in class com.yahoo.labs.samoa.instances.ArffLoader
-
The instance information.
- instanceInformation - Variable in class com.yahoo.labs.samoa.instances.Instances
-
The instance information.
- instanceInformation - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- instanceInformation - Variable in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- InstanceInformation - Class in com.yahoo.labs.samoa.instances
-
The Class InstanceInformation.
- InstanceInformation() - Constructor for class com.yahoo.labs.samoa.instances.InstanceInformation
-
Instantiates a new instance information.
- InstanceInformation(InstanceInformation) - Constructor for class com.yahoo.labs.samoa.instances.InstanceInformation
-
Instantiates a new instance information.
- InstanceInformation(String, Attribute[]) - Constructor for class com.yahoo.labs.samoa.instances.InstanceInformation
-
Instantiates a new instance information.
- InstanceInformation(String, List<Attribute>) - Constructor for class com.yahoo.labs.samoa.instances.InstanceInformation
-
Instantiates a new instance information.
- instanceLimitOption - Variable in class moa.gui.experimentertab.tasks.EvaluateConceptDrift
-
- instanceLimitOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedChunks
-
Allows to define the maximum number of instances to test/train on (-1 = no limit).
- instanceLimitOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedTestThenTrain
-
- instanceLimitOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequential
-
- instanceLimitOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequentialCV
-
- instanceLimitOption - Variable in class moa.tasks.EvaluateClustering
-
- instanceLimitOption - Variable in class moa.tasks.EvaluateConceptDrift
-
- instanceLimitOption - Variable in class moa.tasks.EvaluateInterleavedChunks
-
Allows to define the maximum number of instances to test/train on (-1 = no limit).
- instanceLimitOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- instanceLimitOption - Variable in class moa.tasks.EvaluatePrequential
-
- instanceLimitOption - Variable in class moa.tasks.EvaluatePrequentialCV
-
- instanceLimitOption - Variable in class moa.tasks.EvaluatePrequentialDelayed
-
- instanceLimitOption - Variable in class moa.tasks.EvaluatePrequentialDelayedCV
-
- instanceLimitOption - Variable in class moa.tasks.EvaluatePrequentialMultiLabel
-
- instanceLimitOption - Variable in class moa.tasks.EvaluatePrequentialMultiTarget
-
- instanceLimitOption - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- instanceLimitOption - Variable in class moa.tasks.EvaluatePrequentialRegression
-
- instanceLimitOption - Variable in class moa.tasks.meta.ALPrequentialEvaluationTask
-
- InstanceOutputAttributesSelector - Class in moa.classifiers.rules.multilabel.instancetransformers
-
Transforms instances considering only a subset of output attributes
- InstanceOutputAttributesSelector() - Constructor for class moa.classifiers.rules.multilabel.instancetransformers.InstanceOutputAttributesSelector
-
- InstanceOutputAttributesSelector(InstancesHeader, int[]) - Constructor for class moa.classifiers.rules.multilabel.instancetransformers.InstanceOutputAttributesSelector
-
- instanceRandom - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- instanceRandom - Variable in class moa.streams.generators.AgrawalGenerator
-
- instanceRandom - Variable in class moa.streams.generators.AssetNegotiationGenerator
-
- instanceRandom - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- instanceRandom - Variable in class moa.streams.generators.HyperplaneGenerator
-
- instanceRandom - Variable in class moa.streams.generators.LEDGenerator
-
- instanceRandom - Variable in class moa.streams.generators.MixedGenerator
-
- instanceRandom - Variable in class moa.streams.generators.RandomRBFGenerator
-
- instanceRandom - Variable in class moa.streams.generators.RandomTreeGenerator
-
- instanceRandom - Variable in class moa.streams.generators.SEAGenerator
-
- instanceRandom - Variable in class moa.streams.generators.SineGenerator
-
- instanceRandom - Variable in class moa.streams.generators.STAGGERGenerator
-
- instanceRandom - Variable in class moa.streams.generators.TextGenerator
-
- instanceRandom - Variable in class moa.streams.generators.WaveformGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.AgrawalGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.AssetNegotiationGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.HyperplaneGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.LEDGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.MixedGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.RandomRBFGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.RandomTreeGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.SEAGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.SineGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.STAGGERGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.TextGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.generators.WaveformGenerator
-
- instanceRandomSeedOption - Variable in class moa.streams.ImbalancedStream
-
- instanceRandomSeedOption - Variable in class moa.streams.IrrelevantFeatureAppenderStream
-
- instances - Variable in class com.yahoo.labs.samoa.instances.Instances
-
The instances.
- instances - Variable in class moa.classifiers.meta.PairedLearners
-
- instances - Variable in class moa.streams.ArffFileStream
-
- instances - Variable in class moa.streams.clustering.FileStream
-
- instances - Variable in class moa.streams.MultiTargetArffFileStream
-
- Instances - Class in com.yahoo.labs.samoa.instances
-
The Class Instances.
- Instances() - Constructor for class com.yahoo.labs.samoa.instances.Instances
-
Instantiates a new instances.
- Instances(Instances) - Constructor for class com.yahoo.labs.samoa.instances.Instances
-
Instantiates a new instances.
- Instances(Instances, int) - Constructor for class com.yahoo.labs.samoa.instances.Instances
-
Instantiates a new instances.
- Instances(Instances, int, int) - Constructor for class com.yahoo.labs.samoa.instances.Instances
-
Instantiates a new instances.
- Instances(Reader, int, int) - Constructor for class com.yahoo.labs.samoa.instances.Instances
-
Instantiates a new instances.
- Instances(Reader, Range) - Constructor for class com.yahoo.labs.samoa.instances.Instances
-
Instantiates a new instances.
- Instances(StringReader, int) - Constructor for class com.yahoo.labs.samoa.instances.Instances
-
Instantiates a new instances.
- Instances(String, Attribute[], int) - Constructor for class com.yahoo.labs.samoa.instances.Instances
-
Instantiates a new instances.
- Instances(String, List<Attribute>, int) - Constructor for class com.yahoo.labs.samoa.instances.Instances
-
Instantiates a new instances.
- INSTANCES_BETWEEN_MONITOR_UPDATES - Static variable in class moa.tasks.MainTask
-
The number of instances between monitor updates.
- instancesBuffer - Variable in class moa.classifiers.meta.WEKAClassifier
-
- instancesBuffer - Variable in class moa.classifiers.multilabel.MEKAClassifier
-
- instancesBuffer - Variable in class moa.streams.ImbalancedStream
-
- InstancesHeader - Class in com.yahoo.labs.samoa.instances
-
Class for storing the header or context of a data stream.
- InstancesHeader() - Constructor for class com.yahoo.labs.samoa.instances.InstancesHeader
-
- InstancesHeader(Instances) - Constructor for class com.yahoo.labs.samoa.instances.InstancesHeader
-
- instancesSeen - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- instancesSeen - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- instancesSeen - Variable in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- instancesSeen - Variable in class moa.classifiers.meta.StreamingRandomPatches
-
- instancesSeen - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.MultitargetPerceptron
-
- instancesSeen - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyFading
-
- instancesSeen - Variable in class moa.classifiers.rules.RuleClassification
-
- instancesSeen - Variable in class moa.classifiers.trees.ARFFIMTDD.FIMTDDPerceptron
-
- instancesSeen - Variable in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
-
- instancesSeen - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- instancesSeenTest - Variable in class moa.classifiers.rules.RuleClassification
-
- InstancesSummaryPanel - Class in moa.gui.featureanalysis
-
This panel just displays relation name, number of instances, and number of
attributes.
- InstancesSummaryPanel() - Constructor for class moa.gui.featureanalysis.InstancesSummaryPanel
-
Creates the instances panel with no initial instances.
- InstanceStream - Interface in moa.streams
-
Interface representing a data stream of instances.
- instanceTransformer - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- InstanceTransformer - Interface in moa.classifiers.rules.multilabel.instancetransformers
-
Interface for instance transformation
- instantiationComplete() - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
We've been instantiated and now have access to the main application and
PerspectiveManager
- instNodeCountSinceReal - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- instNodeCountSinceVirtual - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- instSeenSinceLastSplitAttempt - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- instTreeCountSinceReal - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- INT_ADD - Static variable in class moa.clusterers.clustree.util.SimpleBudget
-
- INT_DIV - Static variable in class moa.clusterers.clustree.util.SimpleBudget
-
- INT_MULT - Static variable in class moa.clusterers.clustree.util.SimpleBudget
-
- integerAddition() - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget class that an integer addition has been
performed by the tree.
- integerAddition() - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- integerAddition(int) - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget that a certain number of integer additions
have been done.
- integerAddition(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- integerDivision() - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget class that a integer division has
been performed by the tree.
- integerDivision() - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- integerDivision(int) - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget that a certain number of integer divisions
have been performed.
- integerDivision(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- integerMultiplication() - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget class that a integer multiplicaton has
been performed by the tree.
- integerMultiplication() - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- integerMultiplication(int) - Method in interface moa.clusterers.clustree.util.Budget
-
Inform the Budget that a certain number of integer
multiplications have been performed.
- integerMultiplication(int) - Method in class moa.clusterers.clustree.util.SimpleBudget
-
- IntegerParameter - Class in moa.clusterers.meta
-
- IntegerParameter(IntegerParameter) - Constructor for class moa.clusterers.meta.IntegerParameter
-
- IntegerParameter(ParameterConfiguration) - Constructor for class moa.clusterers.meta.IntegerParameter
-
- interchangedTrees - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- INTERNAL_DRIFT - Static variable in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector.SeqDrift1
-
- IntOption - Class in com.github.javacliparser
-
Int option.
- IntOption(String, char, String, int) - Constructor for class com.github.javacliparser.IntOption
-
- IntOption(String, char, String, int, int, int) - Constructor for class com.github.javacliparser.IntOption
-
- IntOptionEditComponent - Class in com.github.javacliparser.gui
-
An OptionEditComponent that lets the user edit an integer option.
- IntOptionEditComponent(Option) - Constructor for class com.github.javacliparser.gui.IntOptionEditComponent
-
- intToCLIString(int) - Static method in class com.github.javacliparser.IntOption
-
- invalidate() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
invalidates all initializations.
- inverseError(double) - Static method in class moa.clusterers.clustream.ClustreamKernel
-
Approximates the inverse error function.
- InverseErrorWeightedVote - Class in moa.classifiers.rules.core.voting
-
InverseErrorWeightedVoteMultiLabel class for weighted votes based on estimates of errors.
- InverseErrorWeightedVote() - Constructor for class moa.classifiers.rules.core.voting.InverseErrorWeightedVote
-
- InverseErrorWeightedVoteMultiLabel - Class in moa.classifiers.rules.multilabel.core.voting
-
InverseErrorWeightedVoteMuliLabel class for weighted votes based on estimates of errors.
- InverseErrorWeightedVoteMultiLabel() - Constructor for class moa.classifiers.rules.multilabel.core.voting.InverseErrorWeightedVoteMultiLabel
-
- invertedSumariesPerMeasure(String) - Method in class moa.gui.experimentertab.Summary
-
Generates a latex summary, in which the rows are the datasets and the
columns the algorithms.
- invertSelectionTipText() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Returns the tip text for this property.
- IParameter - Interface in moa.clusterers.meta
-
- IrrelevantFeatureAppenderStream - Class in moa.streams
-
IrrelevantFeatureAppender Stream.
- IrrelevantFeatureAppenderStream() - Constructor for class moa.streams.IrrelevantFeatureAppenderStream
-
- isAbove(double) - Method in interface moa.classifiers.active.budget.BudgetManager
-
Returns true if the given value is above an internal threshold and the
label should be acquired.
- isAbove(double) - Method in class moa.classifiers.active.budget.FixedBM
-
- isALeaf() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
Checks if node is a leaf.
- isAllAttUsed() - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- isAnomaly(Instance, double, double, int) - Method in class moa.classifiers.rules.core.Rule
-
- isAnomaly(Instance, double, double, int) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- isAnomaly(Instance, double, double, int) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- isAttChanged() - Method in class moa.clusterers.dstream.CharacteristicVector
-
- ISB - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- ISB - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
-
- ISB - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- ISB_PD - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- isBackgroundLearner - Variable in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- isBackgroundLearner - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- isBackgroundLearner - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- ISBIndex - Class in moa.clusterers.outliers.AbstractC
-
- ISBIndex - Class in moa.clusterers.outliers.Angiulli
-
- ISBIndex - Class in moa.clusterers.outliers.MCOD
-
- ISBIndex - Class in moa.clusterers.outliers.SimpleCOD
-
- ISBIndex(double, double) - Constructor for class moa.clusterers.outliers.AbstractC.ISBIndex
-
- ISBIndex(double, int) - Constructor for class moa.clusterers.outliers.Angiulli.ISBIndex
-
- ISBIndex(double, int) - Constructor for class moa.clusterers.outliers.MCOD.ISBIndex
-
- ISBIndex(double, int) - Constructor for class moa.clusterers.outliers.SimpleCOD.ISBIndex
-
- ISBIndex.ISBNode - Class in moa.clusterers.outliers.AbstractC
-
- ISBIndex.ISBNode - Class in moa.clusterers.outliers.Angiulli
-
- ISBIndex.ISBNode - Class in moa.clusterers.outliers.MCOD
-
- ISBIndex.ISBNode - Class in moa.clusterers.outliers.SimpleCOD
-
- ISBIndex.ISBNode.NodeType - Enum in moa.clusterers.outliers.MCOD
-
- ISBIndex.ISBSearchResult - Class in moa.clusterers.outliers.AbstractC
-
- ISBIndex.ISBSearchResult - Class in moa.clusterers.outliers.Angiulli
-
- ISBIndex.ISBSearchResult - Class in moa.clusterers.outliers.MCOD
-
- ISBIndex.ISBSearchResult - Class in moa.clusterers.outliers.SimpleCOD
-
- ISBNode(Instance, StreamObj, Long) - Constructor for class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
-
- ISBNode(Instance, StreamObj, Long) - Constructor for class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
-
- ISBNode(Instance, StreamObj, Long) - Constructor for class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- ISBNode(Instance, StreamObj, Long) - Constructor for class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- ISBNodeAppr(Instance, StreamObj, Long, int) - Constructor for class moa.clusterers.outliers.Angiulli.ApproxSTORM.ISBNodeAppr
-
- ISBNodeExact(Instance, StreamObj, Long, int) - Constructor for class moa.clusterers.outliers.Angiulli.ExactSTORM.ISBNodeExact
-
- ISBSearchResult(ISBIndex.ISBNode, double) - Constructor for class moa.clusterers.outliers.AbstractC.ISBIndex.ISBSearchResult
-
- ISBSearchResult(ISBIndex.ISBNode, double) - Constructor for class moa.clusterers.outliers.Angiulli.ISBIndex.ISBSearchResult
-
- ISBSearchResult(ISBIndex.ISBNode, double) - Constructor for class moa.clusterers.outliers.MCOD.ISBIndex.ISBSearchResult
-
- ISBSearchResult(ISBIndex.ISBNode, double) - Constructor for class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBSearchResult
-
- isBufferStoring - Variable in class moa.classifiers.meta.WEKAClassifier
-
- isCancelled() - Method in class moa.tasks.NullMonitor
-
- isCancelled() - Method in class moa.tasks.StandardTaskMonitor
-
- isCancelled() - Method in interface moa.tasks.TaskMonitor
-
Gets whether the task monitored is cancelled.
- isCancelled() - Method in class moa.tasks.TaskThread
-
- isCellEditable(int, int) - Method in class moa.gui.active.ALTaskManagerPanel.TaskTableModel
-
- isCellEditable(int, int) - Method in class moa.gui.AuxiliarTaskManagerPanel.TaskTableModel
-
- isCellEditable(int, int) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.TaskTableModel
-
- isCellEditable(int, int) - Method in class moa.gui.experimentertab.TaskManagerTabPanel.TaskTableModel
-
- isCellEditable(int, int) - Method in class moa.gui.LineGraphViewPanel.PlotTableModel
-
- isCellEditable(int, int) - Method in class moa.gui.MultiLabelTaskManagerPanel.TaskTableModel
-
- isCellEditable(int, int) - Method in class moa.gui.MultiTargetTaskManagerPanel.TaskTableModel
-
- isCellEditable(int, int) - Method in class moa.gui.RegressionTaskManagerPanel.TaskTableModel
-
- isCellEditable(int, int) - Method in class moa.gui.TaskManagerPanel.TaskTableModel
-
- isChangeDetected - Variable in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Change was detected
- isChangeDetected() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- isClassificationEnabled - Variable in class moa.classifiers.meta.WEKAClassifier
-
- isClassificationEnabled - Variable in class moa.classifiers.multilabel.MEKAClassifier
-
- isClustered() - Method in class moa.clusterers.macro.dbscan.DenseMicroCluster
-
- isComplete - Variable in class moa.tasks.StandardTaskMonitor
-
- isComplete() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- isComplete() - Method in class moa.tasks.TaskThread
-
- isCompleted - Variable in class moa.gui.experimentertab.ExpTaskThread
-
- isConnected() - Method in class moa.clusterers.dstream.GridCluster
-
Tests a grid cluster for connectedness according to Definition 3.4, Grid Group, from
Chen and Tu 2007.
- isCovering(Instance) - Method in class moa.classifiers.rules.core.Rule
-
- isCovering(MultiLabelInstance) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- isDate - Variable in class com.yahoo.labs.samoa.instances.Attribute
-
The is date.
- isDefault - Variable in class moa.clusterers.meta.Algorithm
-
- isDense(double) - Method in class moa.clusterers.dstream.CharacteristicVector
-
Implements the test for whether a density grid is dense given
in eq 8 of Chen and Tu 2007.
- isEmpty() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
Gets whether the list is empty.
- isEmpty() - Method in class moa.clusterers.clustream.ClustreamKernel
-
Check if this cluster is empty or not.
- isEmpty() - Method in class moa.clusterers.clustree.ClusKernel
-
Check if this cluster is empty or not.
- isEmpty() - Method in class moa.clusterers.clustree.Entry
-
Check if this Entry is empty or not.
- isEmpty() - Method in class moa.clusterers.kmeanspm.CuckooHashing
-
Returns true if this hash table contains no elements.
- isEnabled(int) - Method in class moa.evaluation.MeasureCollection
-
- isEnabledDrawClustering() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- isEnabledDrawGroundTruth() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- isEnabledDrawMicroclustering() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- isEnabledDrawOutliers() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- isEnabledDrawPoints() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- isEnabledDrawPoints() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- isEqual(NumericAttributeBinaryRulePredicate) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- isEqualOrLess() - Method in class moa.classifiers.rules.core.conditionaltests.NominalAttributeBinaryRulePredicate
-
- isEqualOrLess() - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- isEqualOrLess() - Method in class moa.classifiers.rules.core.NominalRulePredicate
-
- isEqualOrLess() - Method in class moa.classifiers.rules.core.NumericRulePredicate
-
- isEqualOrLess() - Method in interface moa.classifiers.rules.core.Predicate
-
- isEqualsPassesTest() - Method in class moa.classifiers.trees.iadem.IademNumericAttributeBinaryTest
-
- isFailed() - Method in class moa.tasks.TaskThread
-
- isFirstAfterExpansion() - Method in class moa.classifiers.rules.featureranking.MeritFeatureRanking.RuleInformation
-
- isFull() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- isGroundTruth() - Method in class moa.cluster.Cluster
-
- isIncludedInRuleNode(NumericAttributeBinaryRulePredicate) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- isInitialized - Variable in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
The change detector has been initialized with the option values
- isInitialized - Variable in class moa.classifiers.trees.EFDT.ActiveLearningNode
-
- isInitialized - Variable in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
-
- isInside(DensityGrid) - Method in class moa.clusterers.dstream.GridCluster
-
Inside Grids are defined in Definition 3.5 of Chen and Tu 2007 as:
Consider a grid group G and a grid g ∈ G, suppose g =(j1, ··· ,jd), if g has
neighboring grids in every dimension i =1, ·· · ,d, then g is an inside grid
in G.Otherwise g is an outside grid in G.
- isInside(DensityGrid, DensityGrid) - Method in class moa.clusterers.dstream.GridCluster
-
Inside Grids are defined in Definition 3.5 of Chen and Tu 2007 as:
Consider a grid group G and a grid g ∈ G, suppose g =(j1, ··· ,jd), if g has
neighboring grids in every dimension i =1, ·· · ,d, then g is an inside grid
in G.
- isIrrelevant(double) - Method in class moa.clusterers.clustree.Entry
-
Returns true if this entry is irrelevant with respecto the given
threshold.
- isJavaVersionOK() - Static method in class moa.DoTask
-
Checks if the Java version is recent enough to run MOA.
- isLastSubtaskOnLevel - Variable in class moa.tasks.meta.MetaMainTask
-
- isLeaf() - Method in class moa.classifiers.trees.EFDT.Node
-
- isLeaf() - Method in class moa.classifiers.trees.EFDT.SplitNode
-
- isLeaf() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
-
- isLeaf() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- isLeaf() - Method in class moa.classifiers.trees.HoeffdingTree.Node
-
- isLeaf() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- isLeaf() - Method in class moa.clusterers.clustree.Node
-
Checks if this node is a leaf.
- isMetBy(Class<?>) - Method in class moa.capabilities.CapabilityRequirement
-
Tests if the requirement is met by the given class.
- isMetBy(Capabilities) - Method in class moa.capabilities.CapabilityRequirement
-
Tests if the requirement is met by the given set of capabilities.
- isMetBy(CapabilitiesHandler) - Method in class moa.capabilities.CapabilityRequirement
-
Tests if the requirement is met by the given capabilities handler.
- isMissing(int) - Method in class com.yahoo.labs.samoa.instances.DenseInstanceData
-
Checks if is missing.
- isMissing(int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Checks if an attribute is missing.
- isMissing(int) - Method in interface com.yahoo.labs.samoa.instances.InstanceData
-
Checks if is missing.
- isMissing(int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Checks if is missing.
- isMissing(int) - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Checks if is missing.
- isMissing(Attribute) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Checks if an attribute is missing.
- isMissing(Attribute) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- isMissingSparse(int) - Method in class com.yahoo.labs.samoa.instances.DenseInstanceData
-
Checks if is missing sparse.
- isMissingSparse(int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Checks if the attribute is missing sparse.
- isMissingSparse(int) - Method in interface com.yahoo.labs.samoa.instances.InstanceData
-
Checks if is missing sparse.
- isMissingSparse(int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Checks if is missing sparse.
- isMissingSparse(int) - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Checks if is missing sparse.
- isMissingValue(double) - Static method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Tests if the given value codes "missing".
- isMissingValue(double) - Static method in class moa.core.Utils
-
Tests if the given value codes "missing".
- isNextInstanceFromPartition() - Method in class moa.streams.PartitioningStream
-
check if this stream is excluded from seeing the next instance
- IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.Angiulli.STORMBase
-
- IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.AnyOut.AnyOut
-
- IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.MCOD.MCODBase
-
- IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- IsNodeIdInWin(long) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- isNoise() - Method in class moa.gui.visualization.DataPoint
-
- isNominal - Variable in class com.yahoo.labs.samoa.instances.Attribute
-
The is nominal.
- isNominal() - Method in class com.yahoo.labs.samoa.instances.Attribute
-
Checks if is nominal.
- isNullError() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- isNullError() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- isNullError() - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
-
- isNumeric - Variable in class com.yahoo.labs.samoa.instances.Attribute
-
The is numeric.
- isNumeric() - Method in class com.yahoo.labs.samoa.instances.Attribute
-
Checks if is numeric.
- isOnlyBinaryTest() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- isOnlyMultiwayTest() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- ISOUPTree - Class in moa.classifiers.multilabel.trees
-
iSOUPTrees class for structured output prediction.
- ISOUPTree() - Constructor for class moa.classifiers.multilabel.trees.ISOUPTree
-
- ISOUPTree.InnerNode - Class in moa.classifiers.multilabel.trees
-
- ISOUPTree.LeafNode - Class in moa.classifiers.multilabel.trees
-
- ISOUPTree.MultitargetPerceptron - Class in moa.classifiers.multilabel.trees
-
- ISOUPTree.Node - Class in moa.classifiers.multilabel.trees
-
- ISOUPTree.SplitNode - Class in moa.classifiers.multilabel.trees
-
- isOutiler() - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
-
- isOutlier(int) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- isOutputFile - Variable in class com.github.javacliparser.FileOption
-
- isOutputFile() - Method in class com.github.javacliparser.FileOption
-
- isPaintable() - Method in class weka.gui.MOAClassOptionEditor
-
Returns true since this editor is paintable.
- isPaused() - Method in class moa.tasks.NullMonitor
-
- isPaused() - Method in class moa.tasks.StandardTaskMonitor
-
- isPaused() - Method in interface moa.tasks.TaskMonitor
-
Gets whether the task monitored is paused.
- isPositive - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator.Score
-
True if example's true label is positive
- isPositive - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator.Score
-
True if example's true label is positive
- isPresent() - Static method in class moa.core.SizeOf
-
Checks whteher the agent is present.
- isPublicConcreteClassOfType(String, Class<?>) - Static method in class moa.core.AutoClassDiscovery
-
- isRandomizable() - Method in class moa.classifiers.active.ALRandom
-
- isRandomizable() - Method in class moa.classifiers.active.ALUncertainty
-
- isRandomizable() - Method in class moa.classifiers.bayes.NaiveBayes
-
- isRandomizable() - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
-
- isRandomizable() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- isRandomizable() - Method in class moa.classifiers.functions.MajorityClass
-
- isRandomizable() - Method in class moa.classifiers.functions.NoChange
-
- isRandomizable() - Method in class moa.classifiers.functions.Perceptron
-
- isRandomizable() - Method in class moa.classifiers.functions.SGD
-
- isRandomizable() - Method in class moa.classifiers.functions.SGDMultiClass
-
- isRandomizable() - Method in class moa.classifiers.functions.SPegasos
-
- isRandomizable() - Method in class moa.classifiers.lazy.kNN
-
- isRandomizable() - Method in class moa.classifiers.lazy.kNNwithPAW
-
- isRandomizable() - Method in class moa.classifiers.lazy.kNNwithPAWandADWIN
-
- isRandomizable() - Method in class moa.classifiers.lazy.SAMkNN
-
- isRandomizable() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Determines whether the classifier is randomizable.
- isRandomizable() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Determines whether the classifier is randomizable.
- isRandomizable() - Method in class moa.classifiers.meta.AdaptiveRandomForest
-
- isRandomizable() - Method in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- isRandomizable() - Method in class moa.classifiers.meta.ADOB
-
- isRandomizable() - Method in class moa.classifiers.meta.BOLE
-
- isRandomizable() - Method in class moa.classifiers.meta.DACC
-
- isRandomizable() - Method in class moa.classifiers.meta.DynamicWeightedMajority
-
- isRandomizable() - Method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- isRandomizable() - Method in class moa.classifiers.meta.imbalanced.CSMOTE
-
- isRandomizable() - Method in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- isRandomizable() - Method in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- isRandomizable() - Method in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- isRandomizable() - Method in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- isRandomizable() - Method in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- isRandomizable() - Method in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- isRandomizable() - Method in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- isRandomizable() - Method in class moa.classifiers.meta.LearnNSE
-
- isRandomizable() - Method in class moa.classifiers.meta.LeveragingBag
-
- isRandomizable() - Method in class moa.classifiers.meta.LimAttClassifier
-
- isRandomizable() - Method in class moa.classifiers.meta.OCBoost
-
- isRandomizable() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Determines whether the classifier is randomizable.
- isRandomizable() - Method in class moa.classifiers.meta.OnlineSmoothBoost
-
- isRandomizable() - Method in class moa.classifiers.meta.OzaBag
-
- isRandomizable() - Method in class moa.classifiers.meta.OzaBagAdwin
-
- isRandomizable() - Method in class moa.classifiers.meta.OzaBagASHT
-
- isRandomizable() - Method in class moa.classifiers.meta.OzaBoost
-
- isRandomizable() - Method in class moa.classifiers.meta.OzaBoostAdwin
-
- isRandomizable() - Method in class moa.classifiers.meta.PairedLearners
-
- isRandomizable() - Method in class moa.classifiers.meta.RandomRules
-
- isRandomizable() - Method in class moa.classifiers.meta.StreamingRandomPatches
-
- isRandomizable() - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
-
- isRandomizable() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- isRandomizable() - Method in class moa.classifiers.meta.WEKAClassifier
-
- isRandomizable() - Method in class moa.classifiers.multilabel.MajorityLabelset
-
- isRandomizable() - Method in class moa.classifiers.multilabel.MEKAClassifier
-
- isRandomizable() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- isRandomizable() - Method in class moa.classifiers.multitarget.BasicMultiLabelLearner
-
- isRandomizable() - Method in class moa.classifiers.multitarget.BasicMultiTargetRegressor
-
- isRandomizable() - Method in class moa.classifiers.multitarget.functions.MultiTargetNoChange
-
- isRandomizable() - Method in class moa.classifiers.oneclass.Autoencoder
-
Autoencoder is randomizable.
- isRandomizable() - Method in class moa.classifiers.oneclass.HSTrees
-
HSTrees is randomizable.
- isRandomizable() - Method in class moa.classifiers.oneclass.NearestNeighbourDescription
-
Nearest Neighbour Description is not randomizable.
- isRandomizable() - Method in class moa.classifiers.rules.AbstractAMRules
-
description of the Methods used.
- isRandomizable() - Method in class moa.classifiers.rules.AMRulesRegressorOld
-
- isRandomizable() - Method in class moa.classifiers.rules.BinaryClassifierFromRegressor
-
- isRandomizable() - Method in class moa.classifiers.rules.functions.AdaptiveNodePredictor
-
- isRandomizable() - Method in class moa.classifiers.rules.functions.LowPassFilteredLearner
-
- isRandomizable() - Method in class moa.classifiers.rules.functions.Perceptron
-
- isRandomizable() - Method in class moa.classifiers.rules.functions.TargetMean
-
- isRandomizable() - Method in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- isRandomizable() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- isRandomizable() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- isRandomizable() - Method in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- isRandomizable() - Method in class moa.classifiers.rules.multilabel.functions.DominantLabelsClassifier
-
- isRandomizable() - Method in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- isRandomizable() - Method in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- isRandomizable() - Method in class moa.classifiers.rules.RuleClassifier
-
- isRandomizable() - Method in class moa.classifiers.trees.ARFFIMTDD
-
- isRandomizable() - Method in class moa.classifiers.trees.ARFHoeffdingTree
-
- isRandomizable() - Method in class moa.classifiers.trees.DecisionStump
-
- isRandomizable() - Method in class moa.classifiers.trees.EFDT
-
- isRandomizable() - Method in class moa.classifiers.trees.FIMTDD
-
- isRandomizable() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- isRandomizable() - Method in class moa.classifiers.trees.HoeffdingTree
-
- isRandomizable() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- isRandomizable() - Method in class moa.classifiers.trees.LimAttHoeffdingTree
-
- isRandomizable() - Method in class moa.classifiers.trees.RandomHoeffdingTree
-
- isRandomizable() - Method in interface moa.clusterers.Clusterer
-
- isRandomizable() - Method in class moa.clusterers.ClusterGenerator
-
- isRandomizable() - Method in class moa.clusterers.clustream.Clustream
-
- isRandomizable() - Method in class moa.clusterers.clustream.WithKmeans
-
- isRandomizable() - Method in class moa.clusterers.clustree.ClusTree
-
- isRandomizable() - Method in class moa.clusterers.CobWeb
-
- isRandomizable() - Method in class moa.clusterers.denstream.WithDBSCAN
-
- isRandomizable() - Method in class moa.clusterers.dstream.Dstream
-
- isRandomizable() - Method in class moa.clusterers.kmeanspm.BICO
-
- isRandomizable() - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- isRandomizable() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- isRandomizable() - Method in class moa.clusterers.streamkm.StreamKM
-
- isRandomizable() - Method in class moa.clusterers.WekaClusteringAlgorithm
-
- isRandomizable() - Method in class moa.learners.ChangeDetectorLearner
-
- isRandomizable() - Method in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- isRandomizable() - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTree
-
- isRandomizable() - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTreeEnsemble
-
- isRandomizable() - Method in interface moa.learners.Learner
-
Gets whether this learner needs a random seed.
- isRegression - Variable in class moa.classifiers.meta.RandomRules
-
- isRegression - Variable in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- isRegression - Variable in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- isRestartable() - Method in class moa.streams.ArffFileStream
-
- isRestartable() - Method in class moa.streams.BootstrappedStream
-
- isRestartable() - Method in class moa.streams.CachedInstancesStream
-
- isRestartable() - Method in class moa.streams.clustering.FileStream
-
- isRestartable() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- isRestartable() - Method in class moa.streams.clustering.SimpleCSVStream
-
- isRestartable() - Method in class moa.streams.ConceptDriftRealStream
-
- isRestartable() - Method in class moa.streams.ConceptDriftStream
-
- isRestartable() - Method in interface moa.streams.ExampleStream
-
Gets whether this stream can restart.
- isRestartable() - Method in class moa.streams.FilteredStream
-
- isRestartable() - Method in class moa.streams.filters.AbstractMultiLabelStreamFilter
-
- isRestartable() - Method in class moa.streams.filters.AbstractStreamFilter
-
- isRestartable() - Method in class moa.streams.generators.AgrawalGenerator
-
- isRestartable() - Method in class moa.streams.generators.AssetNegotiationGenerator
-
- isRestartable() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- isRestartable() - Method in class moa.streams.generators.HyperplaneGenerator
-
- isRestartable() - Method in class moa.streams.generators.LEDGenerator
-
- isRestartable() - Method in class moa.streams.generators.MixedGenerator
-
- isRestartable() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- isRestartable() - Method in class moa.streams.generators.RandomRBFGenerator
-
- isRestartable() - Method in class moa.streams.generators.RandomTreeGenerator
-
- isRestartable() - Method in class moa.streams.generators.SEAGenerator
-
- isRestartable() - Method in class moa.streams.generators.SineGenerator
-
- isRestartable() - Method in class moa.streams.generators.STAGGERGenerator
-
- isRestartable() - Method in class moa.streams.generators.TextGenerator
-
- isRestartable() - Method in class moa.streams.generators.WaveformGenerator
-
- isRestartable() - Method in class moa.streams.ImbalancedStream
-
- isRestartable() - Method in class moa.streams.IrrelevantFeatureAppenderStream
-
- isRestartable() - Method in class moa.streams.MultiFilteredStream
-
- isRestartable() - Method in class moa.streams.MultiLabelFilteredStream
-
- isRestartable() - Method in class moa.streams.MultiTargetArffFileStream
-
- isRestartable() - Method in class moa.streams.PartitioningStream
-
- isRestaurarVectoresPrediccion() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- isRoot() - Method in class moa.classifiers.trees.EFDT.EFDTLearningNode
-
- isRoot() - Method in interface moa.classifiers.trees.EFDT.EFDTNode
-
- isRoot() - Method in class moa.classifiers.trees.EFDT.EFDTSplitNode
-
- isSet - Variable in class com.github.javacliparser.FlagOption
-
- isSet() - Method in class com.github.javacliparser.FlagOption
-
- isSignicativeBetterThan(double) - Method in class moa.gui.experimentertab.statisticaltests.PValuePerTwoAlgorithm
-
- isSignificantlyGreaterThan(double, double, int, int) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeWeightedVote
-
- isSparse(double) - Method in class moa.clusterers.dstream.CharacteristicVector
-
Implements the test for whether a density grid is sparse given
in eq 9 of Chen and Tu 2007.
- isSpecialization() - Method in class moa.classifiers.rules.featureranking.messages.RuleExpandedMessage
-
- isSporadic() - Method in class moa.clusterers.dstream.CharacteristicVector
-
- isStandardDeviationPainted - Variable in class moa.gui.visualization.AbstractGraphPlot
-
- isSubtask() - Method in class moa.tasks.meta.MetaMainTask
-
Check if the task is a subtask of another parent.
- IsTested() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Block
-
- isTransitional(double, double) - Method in class moa.clusterers.dstream.CharacteristicVector
-
Implements the test for whether a density grid is transitional
given in eq 10 of Chen and Tu 2007.
- isType() - Method in class moa.gui.experimentertab.Measure
-
Returns the type of measure
- isUseless(int) - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveSplitNode
-
- isUsingSameAttribute(NumericAttributeBinaryRulePredicate) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- isValidCluster() - Method in class moa.gui.visualization.ClusterPanel
-
- isValidCluster() - Method in class moa.gui.visualization.OutlierPanel
-
- isVisited() - Method in class moa.clusterers.dstream.DensityGrid
-
- isVisited() - Method in class moa.clusterers.macro.dbscan.DenseMicroCluster
-
- isWarningDetected() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- isWarningZone - Variable in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Warning Zone: after a warning and before a change
- isWarningZone - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- isWekaVersionOK() - Static method in class moa.core.WekaUtils
-
Checks if the Weka version is recent enough to run MOA.
- isWekaVersionOK() - Static method in class moa.DoTask
-
Checks if the Weka version is recent enough to run MOA.
- itemExists(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- itemExists(int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- itemFeature - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- itemID - Variable in class moa.recommender.rc.utils.Rating
-
- itemsStats - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
-
- iterationControl - Variable in class moa.classifiers.active.ALUncertainty
-
- iterationsOption - Variable in class moa.recommender.predictor.BRISMFPredictor
-
- iterator() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
An iterator for the set.
- iterator() - Method in class moa.clusterers.outliers.utils.mtree.MTree.Query
-
- iterator() - Method in class moa.recommender.rc.utils.DenseVector
-
- iterator() - Method in class moa.recommender.rc.utils.SparseVector
-
- iterator() - Method in class moa.recommender.rc.utils.Vector
-
- m_A - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- m_ActiveIndices - Variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
The boolean flags, whether an attribute will be used or not.
- m_ActualClassifier - Variable in class weka.classifiers.meta.MOA
-
the actual moa classifier to use for learning.
- m_ActualGenerator - Variable in class weka.datagenerators.classifiers.classification.MOA
-
the actual data generator.
- m_acuity - Variable in class moa.clusterers.CobWeb
-
Acuity (minimum standard deviation).
- m_allEqualWeights - Variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Do all instances have the same weight
- m_as - Variable in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
This holds the attribute stats of the current attribute on display.
- m_asCache - Variable in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Cache of attribute stats info for the current data set
- m_AttPanel - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Panel to let the user toggle attributes
- m_attribIndex - Variable in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
This holds the index of the current attribute on display and should be set
through setAttribute(int idx).
- m_attributeIndex - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
The attribute index starting from 0
- m_attributeName - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
Attribute name
- m_AttributeNameLab - Variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Displays the name of the relation
- m_attributeNames - Variable in class moa.gui.featureanalysis.FeatureImportanceGraph
-
Attribute names of dataset except the class attribute.
- m_AttributeStats - Variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Cached stats on the attributes we've summarized so far
- m_AttributeTypeLab - Variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Displays the type of attribute
- m_AttSummaryPanel - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Displays summary stats on the selected attribute
- m_AttVisualizePanel - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
The visualization of the attribute values
- m_barRange - Variable in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Contains the range of each bar in a histogram.
- m_bias - Variable in class moa.classifiers.functions.SGD
-
- m_bias - Variable in class moa.classifiers.functions.SGDMultiClass
-
- m_biasVelocity - Variable in class moa.classifiers.functions.AdaGrad
-
- m_BinaryGenerator - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- m_Cache - Static variable in class moa.core.AutoClassDiscovery
-
- m_Capabilities - Variable in class moa.capabilities.Capabilities
-
The set of capabilities.
- m_Classifier - Variable in class weka.classifiers.meta.MOA
-
the moa classifier option (this object is used in the GenericObjectEditor).
- m_classIndex - Variable in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Contains the current class index.
- m_classTotals - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial
-
sum of weight_of_instance * word_count_of_instance for each class
- m_cobwebTree - Variable in class moa.clusterers.CobWeb
-
Holds the root of the Cobweb tree.
- m_colorAttrib - Variable in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
This stores and lets the user select a class attribute.
- m_CustomEditor - Variable in class weka.gui.MOAClassOptionEditor
-
the custom editor.
- m_cutoff - Variable in class moa.clusterers.CobWeb
-
Cutoff (minimum category utility).
- m_data - Variable in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
This holds the current set of instances
- m_data - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
This holds the current set of instances
- m_Data - Variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
the instances used internally.
- m_DateFormat - Variable in class com.yahoo.labs.samoa.instances.Attribute
-
Date format specification for date attributes
- m_Distance - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborNode
-
The distance from the current instance to this neighbor.
- m_DistanceFunction - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
the distance function used.
- m_DistanceList - Variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
Array holding the distances of the nearest neighbours.
- m_Distances - Variable in class moa.classifiers.lazy.neighboursearch.LinearNNSearch
-
Array holding the distances of the nearest neighbours.
- m_DistinctLab - Variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Displays the number of distinct values
- m_doNotNormalizeFeatureScore - Variable in class moa.tasks.FeatureImportanceConfig
-
The default doNotNormalizeFeatureScore parameter for feature importance algorithm.
- m_DontNormalize - Variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
True if normalization is turned off (default false).
- m_EditComponent - Variable in class weka.gui.MOAClassOptionEditor
-
the component for editing.
- m_End - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
The end index of the portion of the master index array,
which stores indices of the instances/points the node
contains.
- m_endIndex - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
The start instance index label to prompt user to input end index number
- m_endInstanceInput - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Format m_intEndIndex
- m_epsilon - Variable in class moa.classifiers.functions.AdaGrad
-
The epsilon value
- m_EuclideanDistance - Variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
The euclidean distance function to use.
- m_EuclideanDistance - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
The distance function used for building the tree.
- m_featureImportance - Variable in class moa.gui.featureanalysis.FeatureImportanceGraph
-
Store feature importance scores.
- m_featureRange - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
The string of feature range.
- m_featureRangeBox - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Set feature range shown in a popup window
In default, Nine plots is shown in every popup window at most.
- m_featureRangeEndIndex - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
The feature range end index.
- m_featureRangeStartIndex - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
The feature range start index.
- m_FileChooser - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
The file chooser for selecting data files
- m_First - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
The first node in the list.
- m_Fraction - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- m_Generator - Variable in class weka.datagenerators.classifiers.classification.MOA
-
for manipulating the generator through the GUI.
- m_graphPanel - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
This panel is used to draw line graphs or scatter diagrams
- m_headerInfo - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial
-
copy of header information for use in toString method
- m_histBarCounts - Variable in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
This array holds the count (or height) for the each of the bars in a
barplot or a histogram.
- m_IncludeAll - Variable in class moa.gui.featureanalysis.AttributeSelectionPanel
-
Press to select all attributes
- m_IncludeAll - Variable in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
Press to select all attributes
- m_Instance - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborNode
-
The neighbor instance.
- m_instances - Variable in class moa.tasks.FeatureImportanceConfig
-
This holds the current set of instances
- m_Instances - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
The instances that'll be used for tree construction.
- m_Instances - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
The neighbourhood of instances to find neighbours in.
- m_Instances - Variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
The instances we're playing with
- m_Instances - Variable in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
The dataset.
- m_Instances - Variable in class moa.gui.featureanalysis.FeatureImportancePanel
-
This holds the current set of instances
- m_Instances - Variable in class moa.gui.featureanalysis.InstancesSummaryPanel
-
The instances we're playing with
- m_Instances - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
The working instances
- m_InstancesTemplate - Variable in class moa.core.utils.Converter
-
- m_InstList - Variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
Indexlist of the instances of this kdtree.
- m_InstList - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
The master index array that'll be reshuffled as nodes
are split and the tree is constructed.
- m_InstSummaryPanel - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Displays simple stats on the working instances
- m_intEndIndex - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
The end instance index of x axis for line graph or scatter diagram
- m_intEndIndex - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
The end instance index of x axis for line graph or scatter diagram
- m_intStartIndex - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
The start instance index of x axis for line graph or scatter diagram
- m_intStartIndex - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
The start instance index of x axis for line graph or scatter diagram
- m_Invert - Variable in class moa.gui.featureanalysis.AttributeSelectionPanel
-
Press to invert the current selection
- m_Invert - Variable in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
Press to invert the current selection
- m_IOThread - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
A thread for loading/saving instances from a file or URL
- m_k - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
-
- m_k - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- m_k - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- m_kNN - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
The number of neighbours to find.
- m_L - Variable in class moa.core.utils.Converter
-
- m_L - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- m_lambda - Variable in class moa.classifiers.functions.SGD
-
The regularization parameter
- m_lambda - Variable in class moa.classifiers.functions.SGDMultiClass
-
The regularization parameter
- m_lambda - Variable in class moa.classifiers.functions.SPegasos
-
The regularization parameter
- m_Last - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
The last node in the list.
- m_learningRate - Variable in class moa.classifiers.functions.SGD
-
The learning rate
- m_learningRate - Variable in class moa.classifiers.functions.SGDMultiClass
-
The learning rate
- m_Left - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
left subtree; contains instances with smaller or equal to split value.
- m_Length - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
The number of nodes to attempt to maintain in the list.
- m_Log - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
The message logger
- m_loss - Variable in class moa.classifiers.functions.SGD
-
The current loss function to minimize
- m_loss - Variable in class moa.classifiers.functions.SGDMultiClass
-
The current loss function to minimize
- m_loss - Variable in class moa.classifiers.functions.SPegasos
-
The current loss function to minimize
- m_MaxDepth - Variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
Tree stats.
- m_MaxInstInLeaf - Variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
maximal number of instances in a leaf.
- m_maxValue - Variable in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
This holds the max value of the current attribute.
- m_MeasurePerformance - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Should we measure Performance.
- m_MetaRandom - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- m_MinBoxRelWidth - Variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
minimal relative width of a KDTree rectangle.
- m_MissingLab - Variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Displays the number of missing values
- m_Model - Variable in class moa.gui.featureanalysis.AttributeSelectionPanel
-
The table model containing attribute names and selection status
- m_Model - Variable in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
The table model containing attribute names and selection status
- m_MultilabelInstancesHeader - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- m_NaNSubstitute - Variable in class moa.tasks.FeatureImportanceConfig
-
When scores of feature importance are NaNs, NaNs will be replaced by NaNSubstitute
shown in feature importance line graph.
- m_nBothInlierOutlier - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- m_nBothInlierOutlier - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
-
- m_nBothInlierOutlier - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- m_nBothInlierOutlier - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- m_Next - Variable in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborNode
-
A link to the next neighbor instance.
- m_NodeNumber - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
node number (only for debug).
- m_NodeRanges - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
lowest and highest value and width (= high - low) for each
dimension.
- m_NodesRectBounds - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
The lo and high bounds of the hyper rectangle described by the
node.
- m_nOnlyInlier - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- m_nOnlyInlier - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
-
- m_nOnlyInlier - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- m_nOnlyInlier - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- m_nOnlyOutlier - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- m_nOnlyOutlier - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
-
- m_nOnlyOutlier - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- m_nOnlyOutlier - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- m_normal - Static variable in class moa.clusterers.CobWeb
-
Normal constant.
- m_NormalizeNodeWidth - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Stores whether if the width of a KDTree
node is normalized or not.
- m_NumAttributesLab - Variable in class moa.gui.featureanalysis.InstancesSummaryPanel
-
Displays the number of attributes
- m_numberMerges - Variable in class moa.clusterers.CobWeb
-
the number of merges that happened
- m_numberOfClusters - Variable in class moa.clusterers.CobWeb
-
Number of clusters (nodes in the tree).
- m_numberOfClustersDetermined - Variable in class moa.clusterers.CobWeb
-
whether the number of clusters was already determined
- m_numberSplits - Variable in class moa.clusterers.CobWeb
-
the number of splits that happened
- m_numClasses - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial
-
number of class values
- m_numInstances - Variable in class moa.classifiers.functions.SGD
-
The number of training instances
- m_numInstances - Variable in class moa.classifiers.functions.SGDMultiClass
-
The number of training instances
- m_NumInstancesLab - Variable in class moa.gui.featureanalysis.InstancesSummaryPanel
-
Displays the number of instances
- m_NumLeaves - Variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
Tree stats.
- m_NumNodes - Variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
Tree stats.
- m_OpenFileBut - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Click to load base instances from a file
- m_outlier - Variable in class moa.gui.visualization.RunOutlierVisualizer
-
- m_PanelJShell - Variable in class moa.gui.ScriptingTabPanel
-
the panel to use.
- m_Pattern - Variable in class moa.gui.featureanalysis.AttributeSelectionPanel
-
Press to enter a perl regular expression for selection
- m_Pattern - Variable in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
Press to enter a perl regular expression for selection
- m_PatternRegEx - Variable in class moa.gui.featureanalysis.AttributeSelectionPanel
-
The current regular expression.
- m_PatternRegEx - Variable in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
The current regular expression.
- m_plotAmplify - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Click to amplify line graph or scatter diagram so that user can see plot more clearly
- m_plotTypeBox - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
plot type drop list:
"plot type: Line graph"
"plot type: Scatter diagram"
"No plot type"
- m_Present - Static variable in class moa.core.SizeOf
-
whether the agent is present.
- m_probOfClass - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial
-
the probability of a class (i.e.
- m_QueryFreq - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
-
- m_radius - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- m_radius - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
-
- m_radius - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- m_radius - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- m_Ranges - Variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
The range of the attributes.
- m_RelationNameLab - Variable in class moa.gui.featureanalysis.InstancesSummaryPanel
-
Displays the name of the relation
- m_RemoveAll - Variable in class moa.gui.featureanalysis.AttributeSelectionPanel
-
Press to deselect all attributes
- m_RemoveAll - Variable in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
Press to deselect all attributes
- m_RemoveButton - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Button for removing attributes
- m_Right - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
right subtree; contains instances with larger than split value.
- m_Root - Variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
The root node of the tree.
- m_samoaToWekaInstanceConverter - Variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
- m_samoaToWekaInstanceConverter - Variable in class moa.gui.featureanalysis.InstancesSummaryPanel
-
- m_samoaToWekaInstanceConverter - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Instance converter from Samoa instance to Weak Instance
- m_SaveBut - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Click to apply filters and save the results
- m_saveInstances - Variable in class moa.clusterers.CobWeb
-
Output instances in graph representation of Cobweb tree (Allows
instances at nodes in the tree to be visualized in the Explorer).
- m_selectedAttributeIndices - Variable in class moa.gui.featureanalysis.FeatureImportanceGraph
-
The selected attribute indices.
- m_selectedAttributeIndices - Variable in class moa.gui.featureanalysis.FeatureImportancePanel
-
The selected attribute indices.
- m_selectedPlotTyeIndex - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
plot type drop list:
"plot type: Line graph"
"plot type: Scatter diagram"
"No plot type"
m_selectedPlotTyeIndex means the selected plot index
- m_selectedPlotTyeItem - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
The string of the the selected plot type such as "plot type: Line graph"
- m_selectedPlotTypeIndex - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
The index of the selected plot type index
- m_sendToPerspective - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
For sending instances to various perspectives/tabs
- m_showZeroInstancesAsUnknown - Variable in class moa.gui.featureanalysis.InstancesSummaryPanel
-
Whether to display 0 or ? for the number of instances in cases where a
dataset has only structure.
- m_SkipIdentical - Variable in class moa.classifiers.lazy.neighboursearch.LinearNNSearch
-
Whether to skip instances from the neighbours that are identical to the query instance.
- m_SplitDim - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
attribute to split on.
- m_Splitter - Variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
The node splitter.
- m_SplitValue - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
value to split on.
- m_Start - Variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
The start index of the portion of the master index array,
which stores the indices of the instances/points the node
contains.
- m_startIndex - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
The start instance index label to prompt user to input start index number
- m_startInstanceInput - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Format m_intStartIndex
- m_StatsTable - Variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Displays other stats in a table
- m_Support - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Manages sending notifications to people when we change the set of working
instances.
- m_t - Variable in class moa.classifiers.functions.SGD
-
Holds the current iteration number
- m_t - Variable in class moa.classifiers.functions.SGDMultiClass
-
Holds the current iteration number
- m_t - Variable in class moa.classifiers.functions.SPegasos
-
Holds the current iteration number
- m_Table - Variable in class moa.gui.featureanalysis.AttributeSelectionPanel
-
The table displaying attribute names and selection status
- m_Table - Variable in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
The table displaying attribute names and selection status
- m_theta - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- m_TopCombinations - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- m_UniqueLab - Variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Displays the number of unique values
- m_Validated - Variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Whether all the necessary preparations have been done.
- m_velocity - Variable in class moa.classifiers.functions.AdaGrad
-
Stores the weights (+ bias in the last element)
- m_visAllGraphBut - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Visualize all line graphs or scatter diagrams, not histograms or bar charts
- m_weights - Variable in class moa.classifiers.functions.SGD
-
Stores the weights (+ bias in the last element)
- m_weights - Variable in class moa.classifiers.functions.SGDMultiClass
-
Stores the weights (+ bias in the last element)
- m_weights - Variable in class moa.classifiers.functions.SPegasos
-
Stores the weights (+ bias in the last element)
- m_wekaToSamoaInstanceConverter - Variable in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Instance converter from Weak instance to Samoa Instance
- m_windowSize - Variable in class moa.gui.featureanalysis.FeatureImportancePanel
-
The default windowSize parameter for feature importance algorithm.
- m_windowSize - Variable in class moa.tasks.FeatureImportanceConfig
-
The default windowSize parameter for feature importance algorithm.
- m_WindowSize - Variable in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- m_WindowSize - Variable in class moa.clusterers.outliers.Angiulli.STORMBase
-
- m_WindowSize - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- m_WindowSize - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- m_wordTotalForClass - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial
-
probability that a word (w) exists in a class (H) (i.e.
- MACHEP - Static variable in class moa.core.Statistics
-
Some constants
- magChangeOption - Variable in class moa.streams.generators.HyperplaneGenerator
-
- main(String[]) - Static method in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- main(String[]) - Static method in class moa.classifiers.core.statisticaltests.Cramer
-
- main(String[]) - Static method in class moa.classifiers.core.statisticaltests.KNN
-
- main(String[]) - Static method in class moa.clusterers.meta.ConfStream
-
- main(String[]) - Static method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- main(String[]) - Static method in class moa.clusterers.meta.TruncatedNormal
-
- main(String[]) - Static method in class moa.clusterers.outliers.AbstractC.Test
-
- main(String[]) - Static method in class moa.clusterers.outliers.Angiulli.Test
-
- main(String[]) - Static method in class moa.clusterers.outliers.MCOD.Test
-
- main(String[]) - Static method in class moa.clusterers.outliers.SimpleCOD.Test
-
- main(String[]) - Static method in class moa.clusterers.outliers.TestSpeed
-
- main(String[]) - Static method in class moa.core.AutoClassDiscovery
-
Outputs all class names below "moa" either to stdout or to the
file provided as first argument.
- main(String[]) - Static method in class moa.DoTask
-
Main method for running tasks from the command line.
- main(String[]) - Static method in class moa.gui.AuxiliarTaskManagerPanel
-
- main(String[]) - Static method in class moa.gui.BatchCmd
-
- main(String[]) - Static method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- main(String[]) - Static method in class moa.gui.experimentertab.AnalyzeTab
-
Main class method.
- main(String[]) - Static method in class moa.gui.experimentertab.ImageTreePanel
-
- main(String[]) - Static method in class moa.gui.experimentertab.PlotTab
-
- main(String[]) - Static method in class moa.gui.experimentertab.SummaryTab
-
The main method
- main(String[]) - Static method in class moa.gui.experimentertab.TaskManagerForm
-
- main(String[]) - Static method in class moa.gui.experimentertab.TaskManagerTabPanel
-
Main method
- main(String[]) - Static method in class moa.gui.featureanalysis.AttributeSelectionPanel
-
Tests the attribute selection panel from the command line.
- main(String[]) - Static method in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Tests out the attribute summary panel from the command line.
- main(String[]) - Static method in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Main method to test this class from command line
- main(String[]) - Static method in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
Tests the attribute selection panel from the command line.
- main(String[]) - Static method in class moa.gui.featureanalysis.FeatureImportancePanel
-
- main(String[]) - Static method in class moa.gui.featureanalysis.InstancesSummaryPanel
-
Tests out the instance summary panel from the command line.
- main(String[]) - Static method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Tests out the instance-preprocessing panel from the command line.
- main(String[]) - Static method in class moa.gui.GUI
-
- main(String[]) - Static method in class moa.gui.GUIDefaults
-
only for testing - prints the content of the props file.
- main(String[]) - Static method in class moa.gui.MultiLabelTaskManagerPanel
-
- main(String[]) - Static method in class moa.gui.MultiTargetTaskManagerPanel
-
- main(String[]) - Static method in class moa.gui.RegressionTaskManagerPanel
-
- main(String[]) - Static method in class moa.gui.TaskLauncher
-
- main(String[]) - Static method in class moa.gui.TaskManagerPanel
-
- main(String[]) - Static method in class moa.MakeObject
-
Main method for writing an object to a file from the command line.
- main(String[]) - Static method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- main(String[]) - Static method in class weka.classifiers.meta.MOA
-
Main method for testing this class.
- main(String[]) - Static method in class weka.datagenerators.classifiers.classification.MOA
-
Main method for executing this class.
- mainFindBestValEntropy(BinaryTreeNumericAttributeClassObserver.Node) - Method in class moa.classifiers.rules.RuleClassifier
-
- MainTask - Class in moa.tasks
-
Abstract Main Task.
- MainTask() - Constructor for class moa.tasks.MainTask
-
- mainTree - Variable in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- maj - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- MajorityClass - Class in moa.classifiers.functions
-
Majority class learner.
- MajorityClass() - Constructor for class moa.classifiers.functions.MajorityClass
-
- majorityClassError - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNodeNBKirkby
-
- majorityClassError - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNodeWeightedVote
-
- majorityClassError - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNBAdaptive
-
- majorityClassError - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNBKirkby
-
- MajorityLabelset - Class in moa.classifiers.multilabel
-
Majority Labelset classifier.
- MajorityLabelset() - Constructor for class moa.classifiers.multilabel.MajorityLabelset
-
- MakeObject - Class in moa
-
Class for writing a MOA object to a file from the command line.
- MakeObject() - Constructor for class moa.MakeObject
-
- makeOlder(long, double) - Method in class moa.clusterers.clustree.ClusKernel
-
Make this cluster older.
- makeOlder(long, double) - Method in class moa.clusterers.clustree.Entry
-
Ages this entrie's data AND buffer according to the given
time and aging constant.
- makeOlder(long, double) - Method in class moa.clusterers.clustree.Node
-
- makeTrue(Instance) - Method in interface moa.streams.generators.AssetNegotiationGenerator.ClassFunction
-
- manageMemory(int, int) - Method in class moa.classifiers.bayes.NaiveBayes
-
- manageMemory(int, int) - Method in class moa.classifiers.rules.RuleClassifier
-
- manager - Variable in class moa.clusterers.streamkm.StreamKM
-
- manipulateIds() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
resets the ids, so that the set contains ids from 0 to noOfObjects-1
- MapUtil() - Constructor for class moa.streams.filters.ReplacingMissingValuesFilter.MapUtil
-
- MarkDownCellBuilder - Class in moa.tasks.ipynb
-
Implement a markdown cell
- MarkDownCellBuilder() - Constructor for class moa.tasks.ipynb.MarkDownCellBuilder
-
- marker - Variable in class moa.classifiers.lazy.kNNwithPAW
-
- marker - Variable in class moa.classifiers.lazy.kNNwithPAWandADWIN
-
- markLastAddedBlock() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- materializeObject() - Method in class com.github.javacliparser.AbstractClassOption
-
Gets a materialized object of this option.
- materializeObject(TaskMonitor, ObjectRepository) - Method in class moa.options.AbstractClassOption
-
Gets a materialized object of this option.
- matrixCodes - Variable in class moa.classifiers.meta.LeveragingBag
-
- matrixCodes - Variable in class moa.classifiers.meta.LimAttClassifier
-
- matrixCodes - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- maturityOption - Variable in class moa.classifiers.meta.DACC
-
Maturity age of classifiers
- max - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- MAX - Static variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
The index of MAX value in attributes' range array.
- MAX - Static variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Index of max value in an array of attributes' range.
- MAX_PANEL_HEIGHT - Static variable in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- MAX_STATUS_STRING_LENGTH - Static variable in class moa.DoTask
-
Maximum length of the status string that shows the progress of tasks running.
- MAX_STATUS_STRING_LENGTH - Static variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
Maximum length of the status string that shows the progress of tasks
running.
- max_x_value - Variable in class moa.gui.visualization.AbstractGraphAxes
-
- max_x_value - Variable in class moa.gui.visualization.AbstractGraphCanvas
-
- max_x_value - Variable in class moa.gui.visualization.AbstractGraphPlot
-
- max_y_value - Variable in class moa.gui.visualization.AbstractGraphAxes
-
- max_y_value - Variable in class moa.gui.visualization.AbstractGraphCanvas
-
- max_y_value - Variable in class moa.gui.visualization.AbstractGraphPlot
-
- maxBranches() - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalBinaryTest
-
- maxBranches() - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalTest
-
Gets the number of maximum branches, -1 if unknown.
- maxBranches() - Method in class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
-
- maxBranches() - Method in class moa.classifiers.trees.iadem.IademNominalAttributeMultiwayTest
-
- MAXBUCKETS - Static variable in class moa.classifiers.core.driftdetection.ADWIN
-
- maxBucketsize - Variable in class moa.clusterers.streamkm.BucketManager
-
- maxByteSizeOption - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Determines the maximum size of model (evaluated after every chunk).
- maxByteSizeOption - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Determines the maximum size of model (evaluated after every chunk).
- maxByteSizeOption - Variable in class moa.classifiers.trees.EFDT
-
- maxByteSizeOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- maxByteSizeOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- maxDepthOption - Variable in class moa.classifiers.oneclass.HSTrees
-
- maxExpertsOption - Variable in class moa.classifiers.meta.DynamicWeightedMajority
-
- maxFeaturesDebugOption - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- MAXGAM - Static variable in class moa.core.Statistics
-
- maxHeight - Variable in class moa.clusterers.clustree.ClusTree
-
The maximal height of the tree.
- maxHeightOption - Variable in class moa.clusterers.clustree.ClusTree
-
- maxID - Variable in class moa.classifiers.multilabel.trees.ISOUPTree
-
- maxID - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- maxID - Variable in class moa.classifiers.trees.FIMTDD
-
- maximumCacheSizeOption - Variable in class moa.tasks.CacheShuffledStream
-
- maxIndex() - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- maxIndex() - Method in class moa.core.DoubleVector
-
- maxIndex(double[]) - Static method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- maxIndex(double[]) - Static method in class moa.core.MiscUtils
-
Returns index of maximum element in a given array of doubles.
- maxIndex(double[]) - Static method in class moa.core.Utils
-
Returns index of maximum element in a given
array of doubles.
- maxIndex(int[]) - Static method in class moa.core.Utils
-
Returns index of maximum element in a given
array of integers.
- maxInstanceLimitBatch - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- maxInstanceLimitBatchOption - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- maxInstanceLimitResetBatch - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- maxInstanceLimitResetBatchOption - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- maxInstancesOption - Variable in class moa.tasks.EvaluateModel
-
- maxInstancesOption - Variable in class moa.tasks.EvaluateModelMultiLabel
-
- maxInstancesOption - Variable in class moa.tasks.EvaluateModelMultiTarget
-
- maxInstancesOption - Variable in class moa.tasks.EvaluateModelRegression
-
- maxInstancesOption - Variable in class moa.tasks.LearnModel
-
- maxInstancesOption - Variable in class moa.tasks.LearnModelMultiLabel
-
- maxInstancesOption - Variable in class moa.tasks.LearnModelMultiTarget
-
- maxInstancesOption - Variable in class moa.tasks.LearnModelRegression
-
- maxInstancesOption - Variable in class moa.tasks.WriteMultipleStreamsToARFF
-
- maxInstancesOption - Variable in class moa.tasks.WriteStreamToARFFFile
-
- maxInstInLeafTipText() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Tip text for this property.
- MAXLOG - Static variable in class moa.core.Statistics
-
- maxMemberCount - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- maxMemoryOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedChunks
-
Allows to define the memory limit for the created model.
- maxMemoryOption - Variable in class moa.tasks.EvaluateInterleavedChunks
-
Allows to define the memory limit for the created model.
- maxMOption - Variable in class moa.classifiers.core.statisticaltests.Cramer
-
- maxNestingLevelOption - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- maxNodeCapacity - Variable in class moa.clusterers.outliers.utils.mtree.MTree
-
- maxNodes - Variable in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver
-
- maxNodes - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- maxNodes - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- maxNodesOption - Variable in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver
-
- maxNodesOption - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- maxNodesOption - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- maxNumberOfObservation(int) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaQuantileSummary
-
- maxNumClusterFeatures - Variable in class moa.clusterers.kmeanspm.BICO
-
- maxNumClusterFeaturesOption - Variable in class moa.clusterers.kmeanspm.BICO
-
- maxNumKernelsOption - Variable in class moa.clusterers.clustream.Clustream
-
- maxNumKernelsOption - Variable in class moa.clusterers.clustream.WithKmeans
-
- maxOptionLevelOption - Variable in class moa.classifiers.trees.ORTO
-
- maxOptionPathsOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- MAXPERMANENT - Static variable in class moa.classifiers.meta.ADACC
-
Maximum number of snapshots (copies of classifiers kept in case of recurrence)
- maxPosterior - Variable in class moa.classifiers.active.ALUncertainty
-
- maxPredictionPaths - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- maxRating - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
-
- maxSize - Variable in class moa.classifiers.trees.ASHoeffdingTree
-
- maxSizeConceptOption - Variable in class moa.classifiers.core.driftdetection.RDDM
-
- maxStoredCount - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- maxSubtreesPerNodeOption - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- maxTreeDepthOption - Variable in class moa.streams.generators.RandomTreeGenerator
-
- maxTreesOption - Variable in class moa.classifiers.trees.ORTO
-
- maxVal - Variable in class com.github.javacliparser.FloatOption
-
- maxVal - Variable in class com.github.javacliparser.IntOption
-
- maxValueObservedPerClass - Variable in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- mc - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- mcc - Variable in class moa.clusterers.outliers.MCOD.MicroCluster
-
- mcCorrectWeight - Variable in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
-
- mcCorrectWeight - Variable in class moa.classifiers.trees.ARFHoeffdingTree.LearningNodeNBAdaptive
-
- mcCorrectWeight - Variable in class moa.classifiers.trees.EFDT.LearningNodeNBAdaptive
-
- mcCorrectWeight - Variable in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNBAdaptive
-
- mcCorrectWeight - Variable in class moa.classifiers.trees.HoeffdingTree.LearningNodeNBAdaptive
-
- mcCorrectWeight - Variable in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNBAdaptive
-
- mcCorrectWeight - Variable in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNBAdaptive
-
- MCOD - Class in moa.clusterers.outliers.MCOD
-
- MCOD() - Constructor for class moa.clusterers.outliers.MCOD.MCOD
-
- MCODBase - Class in moa.clusterers.outliers.MCOD
-
- MCODBase() - Constructor for class moa.clusterers.outliers.MCOD.MCODBase
-
- MCODBase.EventItem - Class in moa.clusterers.outliers.MCOD
-
- MCODBase.EventQueue - Class in moa.clusterers.outliers.MCOD
-
- mean - Variable in class moa.core.GaussianEstimator
-
- mean - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- mean(double[]) - Static method in class moa.core.Utils
-
Computes the mean for an array of doubles.
- MeanAbsoluteDeviation - Class in moa.classifiers.rules.errormeasurers
-
Computes the Mean Absolute Deviation for single target regression problems
- MeanAbsoluteDeviation() - Constructor for class moa.classifiers.rules.errormeasurers.MeanAbsoluteDeviation
-
- MeanAbsoluteDeviationMT - Class in moa.classifiers.rules.multilabel.errormeasurers
-
Mean Absolute Deviation for multitarget and with fading factor
- MeanAbsoluteDeviationMT() - Constructor for class moa.classifiers.rules.multilabel.errormeasurers.MeanAbsoluteDeviationMT
-
- meanOrMode(int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Mean or mode.
- MeanPreviewCollection - Class in moa.evaluation.preview
-
- MeanPreviewCollection(PreviewCollection<PreviewCollection<Preview>>) - Constructor for class moa.evaluation.preview.MeanPreviewCollection
-
On creation of a MeanPreviewCollection, the mean Previews and
standard deviation Previews are calculated from the given
PreviewCollection by averaging the measurements for all entries over
the different runs that have been performed.
- Measure - Class in moa.gui.experimentertab
-
This class determines the value of each measure for each algorithm
- Measure(String, String, boolean, int) - Constructor for class moa.gui.experimentertab.Measure
-
Measure Constructor
- measureByteSize() - Method in class moa.AbstractMOAObject
-
- measureByteSize() - Method in class moa.classifiers.trees.EFDT
-
- measureByteSize() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- measureByteSize() - Method in class moa.classifiers.trees.HoeffdingTree
-
- measureByteSize() - Method in class moa.core.AutoExpandVector
-
- measureByteSize() - Method in interface moa.MOAObject
-
Gets the memory size of this object.
- measureByteSize(MOAObject) - Static method in class moa.AbstractMOAObject
-
Gets the memory size of an object.
- MeasureCollection - Class in moa.evaluation
-
- MeasureCollection() - Constructor for class moa.evaluation.MeasureCollection
-
- measureMaxDepth() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns the depth of the tree.
- Measurement - Class in moa.core
-
Class for storing an evaluation measurement.
- Measurement(String, double) - Constructor for class moa.core.Measurement
-
- measurementNames - Variable in class moa.evaluation.preview.LearningCurve
-
- measurements - Variable in class moa.evaluation.LearningEvaluation
-
- measurementValues - Variable in class moa.evaluation.preview.LearningCurve
-
- measureName - Variable in class moa.gui.experimentertab.SummaryTable
-
- measureNumLeaves() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns the number of leaves.
- measureObjectByteSize(Serializable) - Static method in class com.github.javacliparser.SerializeUtils
-
- measureObjectByteSize(Serializable) - Static method in class moa.core.SerializeUtils
-
- MeasureOverview - Class in moa.gui.active
-
MeasureOverview provides a graphical overview of the current and mean
measure values during the runtime of a task.
- MeasureOverview(MeasureCollection[], String, double[]) - Constructor for class moa.gui.active.MeasureOverview
-
Creates a new MeasureOverview.
- measurePerformanceTipText() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Returns the tip text for this property.
- measures - Variable in class moa.gui.experimentertab.Algorithm
-
The list of measures per algorithm
- measures - Variable in class moa.gui.experimentertab.ExperimeterCLI
-
- measures - Variable in class moa.gui.experimentertab.SummaryTab
-
- measures - Variable in class moa.gui.visualization.AbstractGraphCanvas
-
- measures - Variable in class moa.gui.visualization.AbstractGraphPlot
-
- measureSelected - Variable in class moa.gui.visualization.AbstractGraphCanvas
-
- measureSelected - Variable in class moa.gui.visualization.AbstractGraphPlot
-
- measureStds - Variable in class moa.gui.visualization.AbstractGraphCanvas
-
- measureStds - Variable in class moa.gui.visualization.AbstractGraphPlot
-
- measureStdSize - Variable in class moa.gui.experimentertab.Algorithm
-
The same size that the measure list
- MeasureStreamSpeed - Class in moa.tasks
-
Task for measuring the speed of the stream.
- MeasureStreamSpeed() - Constructor for class moa.tasks.MeasureStreamSpeed
-
- measureTreeDepth() - Method in class moa.classifiers.trees.EFDT
-
- measureTreeDepth() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- measureTreeDepth() - Method in class moa.classifiers.trees.HoeffdingTree
-
- measureTreeSize() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns the size of the tree.
- median - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- MedianOfWidestDimension - Class in moa.classifiers.lazy.neighboursearch.kdtrees
-
The class that splits a KDTree node based on the median value of a dimension in which the node's points have the widest spread.
For more information see also:
Jerome H.
- MedianOfWidestDimension() - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.MedianOfWidestDimension
-
- medianOption - Variable in class moa.classifiers.lazy.kNN
-
- MEKAClassifier - Class in moa.classifiers.multilabel
-
Wrapper for MEKA classifiers.
- MEKAClassifier() - Constructor for class moa.classifiers.multilabel.MEKAClassifier
-
- memberCountOption - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Number of component classifiers.
- memberCountOption - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Number of component classifiers.
- memberCountOption - Variable in class moa.classifiers.meta.DACC
-
Ensemble size
- memberCountOption - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Number of component classifiers.
- MembershipMatrix - Class in moa.evaluation
-
- MembershipMatrix(Clustering, ArrayList<DataPoint>) - Constructor for class moa.evaluation.MembershipMatrix
-
- memCheckFrequencyOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedChunks
-
Allows to define the frequency of memory checks.
- memCheckFrequencyOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedTestThenTrain
-
- memCheckFrequencyOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequential
-
- memCheckFrequencyOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequentialCV
-
- memCheckFrequencyOption - Variable in class moa.tasks.EvaluateInterleavedChunks
-
Allows to define the frequency of memory checks.
- memCheckFrequencyOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- memCheckFrequencyOption - Variable in class moa.tasks.EvaluatePrequential
-
- memCheckFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialCV
-
- memCheckFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialDelayed
-
- memCheckFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialDelayedCV
-
- memCheckFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialMultiLabel
-
- memCheckFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialMultiTarget
-
- memCheckFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- memCheckFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialRegression
-
- memCheckFrequencyOption - Variable in class moa.tasks.LearnModel
-
- memCheckFrequencyOption - Variable in class moa.tasks.LearnModelMultiLabel
-
- memCheckFrequencyOption - Variable in class moa.tasks.LearnModelMultiTarget
-
- memCheckFrequencyOption - Variable in class moa.tasks.LearnModelRegression
-
- memoryEstimatePeriodOption - Variable in class moa.classifiers.trees.EFDT
-
- memoryEstimatePeriodOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- memoryEstimatePeriodOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- memoryStrategyOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- MemRecommenderData - Class in moa.recommender.data
-
- MemRecommenderData - Class in moa.recommender.rc.data.impl
-
- MemRecommenderData() - Constructor for class moa.recommender.data.MemRecommenderData
-
- MemRecommenderData() - Constructor for class moa.recommender.rc.data.impl.MemRecommenderData
-
- MemRecommenderData.RatingIterator - Class in moa.recommender.rc.data.impl
-
- merge(SphereCluster) - Method in class moa.cluster.SphereCluster
-
- merge(ClusteringFeature) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Merges the ClusteringFeature with an other ClusteringFeature.
- mergeEntries(int, int) - Method in class moa.clusterers.clustree.Node
-
Merge the two entries at the given position.
- mergeResultsOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- mergeWith(Entry) - Method in class moa.clusterers.clustree.Entry
-
Merge this entry witht the given Entry.
- merit - Variable in class moa.classifiers.core.AttributeSplitSuggestion
-
- merit - Variable in class moa.classifiers.rules.multilabel.core.AttributeExpansionSuggestion
-
- MeritCheckMessage - Class in moa.classifiers.rules.featureranking.messages
-
- MeritCheckMessage(DoubleVector) - Constructor for class moa.classifiers.rules.featureranking.messages.MeritCheckMessage
-
- MeritCheckMessage(DoubleVector, boolean[]) - Constructor for class moa.classifiers.rules.featureranking.messages.MeritCheckMessage
-
- MeritFeatureRanking - Class in moa.classifiers.rules.featureranking
-
Merit Feature Ranking method
João Duarte, João Gama,Feature ranking in hoeffding algorithms for regression.
- MeritFeatureRanking() - Constructor for class moa.classifiers.rules.featureranking.MeritFeatureRanking
-
- MeritFeatureRanking.RuleInformation - Class in moa.classifiers.rules.featureranking
-
- meritLowerBound - Variable in class moa.classifiers.trees.iadem.IademAttributeSplitSuggestion
-
- merits - Variable in class moa.classifiers.rules.featureranking.messages.MeritCheckMessage
-
- MeritThreshold - Class in moa.classifiers.rules.multilabel.inputselectors
-
Input selection algorithm based on Merit threshold
- MeritThreshold() - Constructor for class moa.classifiers.rules.multilabel.inputselectors.MeritThreshold
-
- meritThresholdOption - Variable in class moa.classifiers.rules.featureranking.WeightedMajorityFeatureRanking
-
- MetaMainTask - Class in moa.tasks.meta
-
This class provides features for handling tasks in a tree-like
structure of parents and subtasks.
- MetaMainTask() - Constructor for class moa.tasks.meta.MetaMainTask
-
- MetaMultilabelGenerator - Class in moa.streams.generators.multilabel
-
Stream generator for multilabel data.
- MetaMultilabelGenerator() - Constructor for class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- metaRandomSeedOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- Metric - Class in moa.clusterers.kmeanspm
-
Provides methods to calculate different distances of points.
- Metric() - Constructor for class moa.clusterers.kmeanspm.Metric
-
- mFeaturesModeOption - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- mFeaturesModeOption - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- mFeaturesPerTreeSizeOption - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- mFeaturesPerTreeSizeOption - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- MicroCluster - Class in moa.clusterers.denstream
-
- MicroCluster - Class in moa.clusterers.outliers.MCOD
-
- MicroCluster(double[], int, long, double, Timestamp) - Constructor for class moa.clusterers.denstream.MicroCluster
-
- MicroCluster(Instance, int, long, double, Timestamp) - Constructor for class moa.clusterers.denstream.MicroCluster
-
- MicroCluster(ISBIndex.ISBNode) - Constructor for class moa.clusterers.outliers.MCOD.MicroCluster
-
- MidPointOfWidestDimension - Class in moa.classifiers.lazy.neighboursearch.kdtrees
-
The class that splits a KDTree node based on the midpoint value of a dimension in which the node's points have the widest spread.
For more information see also:
Andrew Moore (1991).
- MidPointOfWidestDimension() - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.MidPointOfWidestDimension
-
- midUpdate - Variable in class com.github.javacliparser.gui.ClassOptionEditComponent
-
Flag that says the text field is in the middle of an update operation.
- MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.active.ALTaskManagerPanel
-
- MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.AuxiliarTaskManagerPanel
-
- MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.MultiLabelTaskManagerPanel
-
- MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.MultiTargetTaskManagerPanel
-
- MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.RegressionTaskManagerPanel
-
- MILLISECS_BETWEEN_REFRESH - Static variable in class moa.gui.TaskManagerPanel
-
- min - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- min - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- MIN - Static variable in class moa.classifiers.lazy.neighboursearch.KDTree
-
The index of MIN value in attributes' range array.
- MIN - Static variable in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Index of min value in an array of attributes' range.
- MIN_VARIANCE - Static variable in class moa.clusterers.clustream.ClustreamKernel
-
- MIN_VARIANCE - Static variable in class moa.clusterers.clustree.ClusKernel
-
- min_x_value - Variable in class moa.gui.visualization.AbstractGraphAxes
-
- min_x_value - Variable in class moa.gui.visualization.AbstractGraphCanvas
-
- min_x_value - Variable in class moa.gui.visualization.AbstractGraphPlot
-
- minBoxRelWidthTipText() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Tip text for this property.
- minBranchFracOption - Variable in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
-
- MinErrorWeightedVote - Class in moa.classifiers.rules.core.voting
-
MinErrorWeightedVote class for weighted votes based on estimates of errors.
- MinErrorWeightedVote() - Constructor for class moa.classifiers.rules.core.voting.MinErrorWeightedVote
-
- Miniball - Class in moa.cluster
-
Java Porting of the Miniball.h code of Bernd Gaertner.
- Miniball(int) - Constructor for class moa.cluster.Miniball
-
- minimumValue - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
-
- minIndex(double[]) - Static method in class moa.core.Utils
-
Returns index of minimum element in a given
array of doubles.
- minIndex(int[]) - Static method in class moa.core.Utils
-
Returns index of minimum element in a given
array of integers.
- minInstanceLimitBatch - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- minInstanceLimitBatchOption - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- minInstanceLimitResetBatch - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- minInstanceLimitResetBatchOption - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- MINLOG - Static variable in class moa.core.Statistics
-
- minMax(Iterable<T>) - Static method in class moa.clusterers.outliers.utils.mtree.utils.Utils
-
Identifies the minimum and maximum elements from an iterable, according
to the natural ordering of the elements.
- minNodeCapacity - Variable in class moa.clusterers.outliers.utils.mtree.MTree
-
- minNumberInstancesOption - Variable in class moa.classifiers.rules.core.anomalydetection.AnomalinessRatioScore
-
- minNumberInstancesOption - Variable in class moa.classifiers.rules.core.anomalydetection.OddsRatioScore
-
- minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.CusumDM
-
- minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.DDM
-
- minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
-
- minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.EWMAChartDM
-
- minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
-
- minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.PageHinkleyDM
-
- minNumInstancesOption - Variable in class moa.classifiers.core.driftdetection.RDDM
-
- minorityInstances - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- minRating - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
-
- minSizeAllowed - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- minSizeAllowedOption - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- minSizeStableConceptOption - Variable in class moa.classifiers.core.driftdetection.RDDM
-
- minSTMSizeOption - Variable in class moa.classifiers.lazy.SAMkNN
-
- minVal - Variable in class com.github.javacliparser.FloatOption
-
- minVal - Variable in class com.github.javacliparser.IntOption
-
- minValueObservedPerClass - Variable in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- minWeight() - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- minWeight() - Method in class moa.core.DoubleVector
-
- MiscUtils - Class in moa.core
-
Class implementing some utility methods.
- MiscUtils() - Constructor for class moa.core.MiscUtils
-
- missingValue() - Static method in class moa.core.Utils
-
Returns the value used to code a missing value.
- missingWeightObserved - Variable in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
-
- MixedGenerator - Class in moa.streams.generators
-
Abrupt concept drift, boolean noise-free examples.
- MixedGenerator() - Constructor for class moa.streams.generators.MixedGenerator
-
- MixedGenerator.ClassFunction - Interface in moa.streams.generators
-
- moa - package moa
-
- MOA - Class in weka.classifiers.meta
-
Wrapper for MOA classifiers.
Since MOA doesn't offer a mechanism to query a classifier for the types of attributes and classes it can handle, the capabilities of this wrapper are hard-coded: nominal and numeric attributes and only nominal class attributes are allowed.
- MOA - Class in weka.datagenerators.classifiers.classification
-
A wrapper around MOA instance streams.
- MOA() - Constructor for class weka.classifiers.meta.MOA
-
- MOA() - Constructor for class weka.datagenerators.classifiers.classification.MOA
-
- moa.capabilities - package moa.capabilities
-
- moa.classifiers - package moa.classifiers
-
- moa.classifiers.active - package moa.classifiers.active
-
- moa.classifiers.active.budget - package moa.classifiers.active.budget
-
- moa.classifiers.bayes - package moa.classifiers.bayes
-
- moa.classifiers.core - package moa.classifiers.core
-
- moa.classifiers.core.attributeclassobservers - package moa.classifiers.core.attributeclassobservers
-
- moa.classifiers.core.conditionaltests - package moa.classifiers.core.conditionaltests
-
- moa.classifiers.core.driftdetection - package moa.classifiers.core.driftdetection
-
- moa.classifiers.core.splitcriteria - package moa.classifiers.core.splitcriteria
-
- moa.classifiers.core.statisticaltests - package moa.classifiers.core.statisticaltests
-
- moa.classifiers.drift - package moa.classifiers.drift
-
- moa.classifiers.functions - package moa.classifiers.functions
-
- moa.classifiers.lazy - package moa.classifiers.lazy
-
- moa.classifiers.lazy.neighboursearch - package moa.classifiers.lazy.neighboursearch
-
- moa.classifiers.lazy.neighboursearch.kdtrees - package moa.classifiers.lazy.neighboursearch.kdtrees
-
- moa.classifiers.meta - package moa.classifiers.meta
-
- moa.classifiers.meta.imbalanced - package moa.classifiers.meta.imbalanced
-
- moa.classifiers.multilabel - package moa.classifiers.multilabel
-
- moa.classifiers.multilabel.core.splitcriteria - package moa.classifiers.multilabel.core.splitcriteria
-
- moa.classifiers.multilabel.meta - package moa.classifiers.multilabel.meta
-
- moa.classifiers.multilabel.trees - package moa.classifiers.multilabel.trees
-
- moa.classifiers.multitarget - package moa.classifiers.multitarget
-
- moa.classifiers.multitarget.functions - package moa.classifiers.multitarget.functions
-
- moa.classifiers.oneclass - package moa.classifiers.oneclass
-
- moa.classifiers.rules - package moa.classifiers.rules
-
- moa.classifiers.rules.core - package moa.classifiers.rules.core
-
- moa.classifiers.rules.core.anomalydetection - package moa.classifiers.rules.core.anomalydetection
-
- moa.classifiers.rules.core.anomalydetection.probabilityfunctions - package moa.classifiers.rules.core.anomalydetection.probabilityfunctions
-
- moa.classifiers.rules.core.attributeclassobservers - package moa.classifiers.rules.core.attributeclassobservers
-
- moa.classifiers.rules.core.changedetection - package moa.classifiers.rules.core.changedetection
-
- moa.classifiers.rules.core.conditionaltests - package moa.classifiers.rules.core.conditionaltests
-
- moa.classifiers.rules.core.splitcriteria - package moa.classifiers.rules.core.splitcriteria
-
- moa.classifiers.rules.core.voting - package moa.classifiers.rules.core.voting
-
- moa.classifiers.rules.driftdetection - package moa.classifiers.rules.driftdetection
-
- moa.classifiers.rules.errormeasurers - package moa.classifiers.rules.errormeasurers
-
- moa.classifiers.rules.featureranking - package moa.classifiers.rules.featureranking
-
- moa.classifiers.rules.featureranking.messages - package moa.classifiers.rules.featureranking.messages
-
- moa.classifiers.rules.functions - package moa.classifiers.rules.functions
-
- moa.classifiers.rules.meta - package moa.classifiers.rules.meta
-
- moa.classifiers.rules.multilabel - package moa.classifiers.rules.multilabel
-
- moa.classifiers.rules.multilabel.attributeclassobservers - package moa.classifiers.rules.multilabel.attributeclassobservers
-
- moa.classifiers.rules.multilabel.core - package moa.classifiers.rules.multilabel.core
-
- moa.classifiers.rules.multilabel.core.splitcriteria - package moa.classifiers.rules.multilabel.core.splitcriteria
-
- moa.classifiers.rules.multilabel.core.voting - package moa.classifiers.rules.multilabel.core.voting
-
- moa.classifiers.rules.multilabel.errormeasurers - package moa.classifiers.rules.multilabel.errormeasurers
-
- moa.classifiers.rules.multilabel.functions - package moa.classifiers.rules.multilabel.functions
-
- moa.classifiers.rules.multilabel.inputselectors - package moa.classifiers.rules.multilabel.inputselectors
-
- moa.classifiers.rules.multilabel.instancetransformers - package moa.classifiers.rules.multilabel.instancetransformers
-
- moa.classifiers.rules.multilabel.meta - package moa.classifiers.rules.multilabel.meta
-
- moa.classifiers.rules.multilabel.outputselectors - package moa.classifiers.rules.multilabel.outputselectors
-
- moa.classifiers.trees - package moa.classifiers.trees
-
- moa.classifiers.trees.iadem - package moa.classifiers.trees.iadem
-
- moa.cluster - package moa.cluster
-
- moa.clusterers - package moa.clusterers
-
- moa.clusterers.clustream - package moa.clusterers.clustream
-
- moa.clusterers.clustree - package moa.clusterers.clustree
-
- moa.clusterers.clustree.util - package moa.clusterers.clustree.util
-
- moa.clusterers.denstream - package moa.clusterers.denstream
-
- moa.clusterers.dstream - package moa.clusterers.dstream
-
- moa.clusterers.kmeanspm - package moa.clusterers.kmeanspm
-
- moa.clusterers.macro - package moa.clusterers.macro
-
- moa.clusterers.macro.dbscan - package moa.clusterers.macro.dbscan
-
- moa.clusterers.meta - package moa.clusterers.meta
-
- moa.clusterers.outliers - package moa.clusterers.outliers
-
- moa.clusterers.outliers.AbstractC - package moa.clusterers.outliers.AbstractC
-
- moa.clusterers.outliers.Angiulli - package moa.clusterers.outliers.Angiulli
-
- moa.clusterers.outliers.AnyOut - package moa.clusterers.outliers.AnyOut
-
- moa.clusterers.outliers.AnyOut.util - package moa.clusterers.outliers.AnyOut.util
-
- moa.clusterers.outliers.MCOD - package moa.clusterers.outliers.MCOD
-
- moa.clusterers.outliers.SimpleCOD - package moa.clusterers.outliers.SimpleCOD
-
- moa.clusterers.outliers.utils.mtree - package moa.clusterers.outliers.utils.mtree
-
- moa.clusterers.outliers.utils.mtree.utils - package moa.clusterers.outliers.utils.mtree.utils
-
- moa.clusterers.streamkm - package moa.clusterers.streamkm
-
- moa.core - package moa.core
-
- moa.core.utils - package moa.core.utils
-
- moa.evaluation - package moa.evaluation
-
- moa.evaluation.preview - package moa.evaluation.preview
-
- moa.gui - package moa.gui
-
- moa.gui.active - package moa.gui.active
-
- moa.gui.clustertab - package moa.gui.clustertab
-
- moa.gui.colorGenerator - package moa.gui.colorGenerator
-
- moa.gui.conceptdrift - package moa.gui.conceptdrift
-
- moa.gui.experimentertab - package moa.gui.experimentertab
-
- moa.gui.experimentertab.statisticaltests - package moa.gui.experimentertab.statisticaltests
-
- moa.gui.experimentertab.tasks - package moa.gui.experimentertab.tasks
-
- moa.gui.featureanalysis - package moa.gui.featureanalysis
-
- moa.gui.outliertab - package moa.gui.outliertab
-
- moa.gui.visualization - package moa.gui.visualization
-
- moa.learners - package moa.learners
-
- moa.learners.featureanalysis - package moa.learners.featureanalysis
-
- moa.options - package moa.options
-
- moa.recommender.data - package moa.recommender.data
-
- moa.recommender.dataset - package moa.recommender.dataset
-
- moa.recommender.dataset.impl - package moa.recommender.dataset.impl
-
- moa.recommender.predictor - package moa.recommender.predictor
-
- moa.recommender.rc.data - package moa.recommender.rc.data
-
- moa.recommender.rc.data.impl - package moa.recommender.rc.data.impl
-
- moa.recommender.rc.predictor - package moa.recommender.rc.predictor
-
- moa.recommender.rc.predictor.impl - package moa.recommender.rc.predictor.impl
-
- moa.recommender.rc.utils - package moa.recommender.rc.utils
-
- moa.streams - package moa.streams
-
- moa.streams.clustering - package moa.streams.clustering
-
- moa.streams.filters - package moa.streams.filters
-
- moa.streams.generators - package moa.streams.generators
-
- moa.streams.generators.cd - package moa.streams.generators.cd
-
- moa.streams.generators.multilabel - package moa.streams.generators.multilabel
-
- moa.tasks - package moa.tasks
-
- moa.tasks.ipynb - package moa.tasks.ipynb
-
- moa.tasks.meta - package moa.tasks.meta
-
- MOAClassOptionEditor - Class in weka.gui
-
An editor for MOA ClassOption objects.
- MOAClassOptionEditor() - Constructor for class weka.gui.MOAClassOptionEditor
-
- MOAObject - Interface in moa
-
Interface implemented by classes in MOA, so that all are serializable,
can produce copies of their objects, and can measure its memory size.
- MOAUtils - Class in weka.core
-
A helper class for MOA related classes.
- MOAUtils() - Constructor for class weka.core.MOAUtils
-
- modelAttIndexToInstanceAttIndex(int, Instance) - Static method in class moa.classifiers.AbstractClassifier
-
Gets the index of the attribute in the instance,
given the index of the attribute in the learner.
- modelAttIndexToInstanceAttIndex(int, Instance) - Static method in class moa.classifiers.rules.AbstractAMRules
-
Gets the index of the attribute in the instance,
given the index of the attribute in the learner.
- modelAttIndexToInstanceAttIndex(int, Instance) - Static method in class moa.clusterers.AbstractClusterer
-
- modelAttIndexToInstanceAttIndex(int, Instances) - Static method in class moa.classifiers.AbstractClassifier
-
Gets the index of the attribute in a set of instances,
given the index of the attribute in the learner.
- modelAttIndexToInstanceAttIndex(int, Instances) - Static method in class moa.clusterers.AbstractClusterer
-
- modelContext - Variable in class moa.classifiers.AbstractClassifier
-
Header of the instances of the data stream
- modelContext - Variable in class moa.clusterers.AbstractClusterer
-
- modelInUse - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- modelOption - Variable in class moa.tasks.EvaluateModel
-
- modelOption - Variable in class moa.tasks.EvaluateModelMultiLabel
-
- modelOption - Variable in class moa.tasks.EvaluateModelMultiTarget
-
- modelOption - Variable in class moa.tasks.EvaluateModelRegression
-
- modelRandomSeedOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- modelRandomSeedOption - Variable in class moa.streams.generators.RandomRBFGenerator
-
- modifyDependencyMatrix(boolean[][], double, Random) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
ModifyDependencyMatrix.
- modifyPriorVector(double[], double, Random, boolean) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
ModifyPriorVector.
- monitorMeanDecr(double, double) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- monitorMeanIncr(double, double) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- moreImprovementsPossible(int, double) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- moreThanOneAttValueObserved() - Method in class moa.classifiers.trees.iadem.Iadem2.NominalVirtualNode
-
- mouseClicked(int, int) - Method in interface moa.gui.AWTInteractiveRenderer
-
- MovielensDataset - Class in moa.recommender.dataset.impl
-
- MovielensDataset() - Constructor for class moa.recommender.dataset.impl.MovielensDataset
-
- mse_r - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
The mean square residual in a given moment, based on a window of latest examples.
- MTRandom - Class in moa.clusterers.streamkm
-
- MTRandom() - Constructor for class moa.clusterers.streamkm.MTRandom
-
The default constructor for an instance of MTRandom.
- MTRandom(boolean) - Constructor for class moa.clusterers.streamkm.MTRandom
-
This version of the constructor can be used to implement identical
behaviour to the original C code version of this algorithm including
exactly replicating the case where the seed value had not been set
prior to calling genrand_int32.
- MTRandom(byte[]) - Constructor for class moa.clusterers.streamkm.MTRandom
-
This version of the constructor initialises the class with the
given byte array.
- MTRandom(int[]) - Constructor for class moa.clusterers.streamkm.MTRandom
-
This version of the constructor initialises the class with the
given integer array.
- MTRandom(long) - Constructor for class moa.clusterers.streamkm.MTRandom
-
This version of the constructor simply initialises the class with
the given 64 bit seed value.
- MTree<DATA> - Class in moa.clusterers.outliers.utils.mtree
-
The main class that implements the M-Tree.
- MTree(int, int, DistanceFunction<? super DATA>, SplitFunction<DATA>) - Constructor for class moa.clusterers.outliers.utils.mtree.MTree
-
Constructs an M-Tree with the specified minimum and maximum node
capacities and distance function.
- MTree(int, DistanceFunction<? super DATA>, SplitFunction<DATA>) - Constructor for class moa.clusterers.outliers.utils.mtree.MTree
-
Constructs an M-Tree with the specified minimum node capacity and
distance function.
- MTree(DistanceFunction<? super DATA>, SplitFunction<DATA>) - Constructor for class moa.clusterers.outliers.utils.mtree.MTree
-
Constructs an M-Tree with the specified distance function.
- MTree.Query - Class in moa.clusterers.outliers.utils.mtree
-
An Iterable class which can be iterated to fetch the results of a
nearest-neighbors query.
- MTree.ResultItem - Class in moa.clusterers.outliers.utils.mtree
-
The type of the results for nearest-neighbor queries.
- mtreeMC - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- mtsknn(List<Instance>, List<Instance>) - Method in class moa.classifiers.core.statisticaltests.KNN
-
- MultiChoiceOption - Class in com.github.javacliparser
-
Multi choice option.
- MultiChoiceOption(String, char, String, String[], String[], int) - Constructor for class com.github.javacliparser.MultiChoiceOption
-
- MultiChoiceOptionEditComponent - Class in com.github.javacliparser.gui
-
An OptionEditComponent that lets the user edit a multi choice option.
- MultiChoiceOptionEditComponent(Option) - Constructor for class com.github.javacliparser.gui.MultiChoiceOptionEditComponent
-
- MultiClassClassifier - Interface in moa.classifiers
-
Multiclass classifier interface for incremental classifier models.
- MultiFilteredStream - Class in moa.streams
-
Class for representing a stream that is filtered.
- MultiFilteredStream() - Constructor for class moa.streams.MultiFilteredStream
-
- MultilabelArffFileStream - Class in moa.streams.generators.multilabel
-
Stream reader for ARFF files of multilabel data.
- MultilabelArffFileStream() - Constructor for class moa.streams.generators.multilabel.MultilabelArffFileStream
-
- MultilabelArffFileStream(String, int) - Constructor for class moa.streams.generators.multilabel.MultilabelArffFileStream
-
- MultiLabelBSTree - Class in moa.classifiers.rules.multilabel.attributeclassobservers
-
Binary search tree for AMRules splitting points determination
- MultiLabelBSTree() - Constructor for class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- MultiLabelBSTree.Node - Class in moa.classifiers.rules.multilabel.attributeclassobservers
-
- MultiLabelBSTreeFloat - Class in moa.classifiers.rules.multilabel.attributeclassobservers
-
- MultiLabelBSTreeFloat() - Constructor for class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- MultiLabelBSTreeFloat.Node - Class in moa.classifiers.rules.multilabel.attributeclassobservers
-
- MultiLabelClassifier - Interface in moa.classifiers
-
- MultiLabelErrorMeasurer - Interface in moa.classifiers.rules.multilabel.errormeasurers
-
- MultiLabelFilteredStream - Class in moa.streams
-
Class for representing a stream that is filtered.
- MultiLabelFilteredStream() - Constructor for class moa.streams.MultiLabelFilteredStream
-
- MultilabelHoeffdingTree - Class in moa.classifiers.multilabel
-
Hoeffding Tree for classifying multi-label data.
- MultilabelHoeffdingTree() - Constructor for class moa.classifiers.multilabel.MultilabelHoeffdingTree
-
- MultilabelHoeffdingTree.MultilabelInactiveLearningNode - Class in moa.classifiers.multilabel
-
- MultilabelHoeffdingTree.MultilabelLearningNodeClassifier - Class in moa.classifiers.multilabel
-
- MultilabelInactiveLearningNode(double[]) - Constructor for class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelInactiveLearningNode
-
- MultilabelInformationGain - Class in moa.classifiers.rules.multilabel.core.splitcriteria
-
Multi-label Information Gain.
- MultilabelInformationGain() - Constructor for class moa.classifiers.rules.multilabel.core.splitcriteria.MultilabelInformationGain
-
- MultilabelInstance - Class in moa.core
-
Multilabel instance.
- MultilabelInstance(double, double[]) - Constructor for class moa.core.MultilabelInstance
-
- MultilabelInstance(InstanceImpl) - Constructor for class moa.core.MultilabelInstance
-
- MultiLabelInstance - Interface in com.yahoo.labs.samoa.instances
-
The Interface MultiLabelInstance.
- MultilabelInstancesHeader - Class in moa.core
-
Class for storing the header or context of a multilabel data stream.
- MultilabelInstancesHeader(Instances, int) - Constructor for class moa.core.MultilabelInstancesHeader
-
- MultiLabelLearner - Interface in moa.classifiers
-
- MultilabelLearningNodeClassifier(double[], Classifier, MultilabelHoeffdingTree) - Constructor for class moa.classifiers.multilabel.MultilabelHoeffdingTree.MultilabelLearningNodeClassifier
-
- MultiLabelMainTask - Class in moa.tasks
-
- MultiLabelMainTask() - Constructor for class moa.tasks.MultiLabelMainTask
-
- MultiLabelNaiveBayes - Class in moa.classifiers.rules.multilabel.functions
-
Binary relevance with Naive Bayes
- MultiLabelNaiveBayes() - Constructor for class moa.classifiers.rules.multilabel.functions.MultiLabelNaiveBayes
-
- MultiLabelNominalAttributeObserver - Class in moa.classifiers.rules.multilabel.attributeclassobservers
-
Function for determination of splitting points for nominal variables
- MultiLabelNominalAttributeObserver() - Constructor for class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelNominalAttributeObserver
-
- MultiLabelPerceptronClassification - Class in moa.classifiers.rules.multilabel.functions
-
Multi-Label perceptron classifier (by Binary Relevance).
- MultiLabelPerceptronClassification() - Constructor for class moa.classifiers.rules.multilabel.functions.MultiLabelPerceptronClassification
-
- MultiLabelPerformanceEvaluator - Interface in moa.evaluation
-
Interface implemented by learner evaluators to monitor
the results of the regression learning process.
- MultiLabelPrediction - Class in com.yahoo.labs.samoa.instances
-
- MultiLabelPrediction() - Constructor for class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- MultiLabelPrediction(int) - Constructor for class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- MultiLabelRandomAMRules - Class in moa.classifiers.rules.multilabel.meta
-
- MultiLabelRandomAMRules() - Constructor for class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- MultiLabelRule - Class in moa.classifiers.rules.multilabel.core
-
- MultiLabelRule() - Constructor for class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- MultiLabelRule(int) - Constructor for class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- MultiLabelRule(LearningLiteral) - Constructor for class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- MultiLabelRuleClassification - Class in moa.classifiers.rules.multilabel.core
-
- MultiLabelRuleClassification() - Constructor for class moa.classifiers.rules.multilabel.core.MultiLabelRuleClassification
-
- MultiLabelRuleClassification(int) - Constructor for class moa.classifiers.rules.multilabel.core.MultiLabelRuleClassification
-
- MultiLabelRuleClassification(LearningLiteralClassification) - Constructor for class moa.classifiers.rules.multilabel.core.MultiLabelRuleClassification
-
- MultiLabelRuleRegression - Class in moa.classifiers.rules.multilabel.core
-
- MultiLabelRuleRegression() - Constructor for class moa.classifiers.rules.multilabel.core.MultiLabelRuleRegression
-
- MultiLabelRuleRegression(int) - Constructor for class moa.classifiers.rules.multilabel.core.MultiLabelRuleRegression
-
- MultiLabelRuleRegression(LearningLiteralRegression) - Constructor for class moa.classifiers.rules.multilabel.core.MultiLabelRuleRegression
-
- MultiLabelRuleSet - Class in moa.classifiers.rules.multilabel.core
-
- MultiLabelRuleSet() - Constructor for class moa.classifiers.rules.multilabel.core.MultiLabelRuleSet
-
- MultiLabelSplitCriterion - Interface in moa.classifiers.rules.multilabel.core.splitcriteria
-
- MultiLabelStreamFilter - Interface in moa.streams.filters
-
- multilabelStreamTemplate - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- MultiLabelTabPanel - Class in moa.gui
-
This panel allows the user to select and configure a task, and run it.
- MultiLabelTabPanel() - Constructor for class moa.gui.MultiLabelTabPanel
-
- MultiLabelTaskManagerPanel - Class in moa.gui
-
This panel displays the running tasks.
- MultiLabelTaskManagerPanel() - Constructor for class moa.gui.MultiLabelTaskManagerPanel
-
- MultiLabelTaskManagerPanel.ProgressCellRenderer - Class in moa.gui
-
- MultiLabelTaskManagerPanel.TaskTableModel - Class in moa.gui
-
- MultiLabelVote - Class in moa.classifiers.rules.multilabel.core.voting
-
- MultiLabelVote(Prediction, double) - Constructor for class moa.classifiers.rules.multilabel.core.voting.MultiLabelVote
-
- multiParamTaskOption - Variable in class moa.tasks.meta.ALPartitionEvaluationTask
-
- MultiTargetArffFileStream - Class in moa.streams
-
Stream reader of ARFF files.
- MultiTargetArffFileStream() - Constructor for class moa.streams.MultiTargetArffFileStream
-
- MultiTargetArffFileStream(String, String) - Constructor for class moa.streams.MultiTargetArffFileStream
-
- MultiTargetArffLoader - Class in com.yahoo.labs.samoa.instances
-
- MultiTargetArffLoader(Reader) - Constructor for class com.yahoo.labs.samoa.instances.MultiTargetArffLoader
-
- MultiTargetArffLoader(Reader, Range) - Constructor for class com.yahoo.labs.samoa.instances.MultiTargetArffLoader
-
- MultiTargetErrorMeasurer - Interface in moa.classifiers.rules.multilabel.errormeasurers
-
- MultiTargetInstanceStream - Interface in moa.streams
-
Interface representing a data stream of instances.
- MultiTargetLearnerSemiSupervised - Interface in moa.classifiers
-
- MultiTargetMainTask - Class in moa.tasks
-
- MultiTargetMainTask() - Constructor for class moa.tasks.MultiTargetMainTask
-
- MultiTargetMeanRegressor - Class in moa.classifiers.rules.multilabel.functions
-
Target mean regressor
- MultiTargetMeanRegressor() - Constructor for class moa.classifiers.rules.multilabel.functions.MultiTargetMeanRegressor
-
- MultiTargetNoChange - Class in moa.classifiers.multitarget.functions
-
MultiTargetNoChange class regressor.
- MultiTargetNoChange() - Constructor for class moa.classifiers.multitarget.functions.MultiTargetNoChange
-
- MultitargetPerceptron(ISOUPTree) - Constructor for class moa.classifiers.multilabel.trees.ISOUPTree.MultitargetPerceptron
-
- MultitargetPerceptron(ISOUPTree, ISOUPTree.MultitargetPerceptron) - Constructor for class moa.classifiers.multilabel.trees.ISOUPTree.MultitargetPerceptron
-
- MultiTargetPerceptronRegressor - Class in moa.classifiers.rules.multilabel.functions
-
Binary relevance with a regression perceptron
- MultiTargetPerceptronRegressor() - Constructor for class moa.classifiers.rules.multilabel.functions.MultiTargetPerceptronRegressor
-
- MultiTargetPerformanceEvaluator - Interface in moa.evaluation
-
Interface implemented by learner evaluators to monitor
the results of the regression learning process.
- MultiTargetRegressor - Interface in moa.classifiers
-
MultiTargetRegressor interface for incremental MultiTarget regression models.
- MultiTargetTabPanel - Class in moa.gui
-
This panel allows the user to select and configure a task, and run it.
- MultiTargetTabPanel() - Constructor for class moa.gui.MultiTargetTabPanel
-
- MultiTargetTaskManagerPanel - Class in moa.gui
-
This panel displays the running tasks.
- MultiTargetTaskManagerPanel() - Constructor for class moa.gui.MultiTargetTaskManagerPanel
-
- MultiTargetTaskManagerPanel.ProgressCellRenderer - Class in moa.gui
-
- MultiTargetTaskManagerPanel.TaskTableModel - Class in moa.gui
-
- MultiTargetVarianceRatio - Class in moa.classifiers.rules.multilabel.core.splitcriteria
-
- MultiTargetVarianceRatio() - Constructor for class moa.classifiers.rules.multilabel.core.splitcriteria.MultiTargetVarianceRatio
-
- MultiTargetWindowRegressionPerformanceEvaluator - Class in moa.evaluation
-
Multi-target regression evaluator that updates evaluation results using a sliding window.
- MultiTargetWindowRegressionPerformanceEvaluator() - Constructor for class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- MultiTargetWindowRegressionPerformanceEvaluator.Estimator - Class in moa.evaluation
-
- MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator - Class in moa.evaluation
-
Multi-target regression evaluator that updates evaluation results using a sliding window.
- MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator() - Constructor for class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator.Estimator - Class in moa.evaluation
-
- multivariateAnomalyProbabilityThresholdOption - Variable in class moa.classifiers.rules.AbstractAMRules
-
- muOption - Variable in class moa.clusterers.denstream.WithDBSCAN
-
- mVisibleColors - Static variable in class moa.clusterers.macro.ColorArray
-
- MyBaseOutlierDetector - Class in moa.clusterers.outliers
-
- MyBaseOutlierDetector() - Constructor for class moa.clusterers.outliers.MyBaseOutlierDetector
-
- MyBaseOutlierDetector.Outlier - Class in moa.clusterers.outliers
-
- MyBaseOutlierDetector.OutlierNotifier - Class in moa.clusterers.outliers
-
- MyBaseOutlierDetector.PrintMsg - Interface in moa.clusterers.outliers
-
- MyBaseOutlierDetector.ProgressInfo - Interface in moa.clusterers.outliers
-
- MyBaseOutlierDetector.StdPrintMsg - Class in moa.clusterers.outliers
-
- MyHeap(int) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap
-
constructor.
- MyHeapElement(int, double) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeapElement
-
constructor.
- myOut - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- myProgressInfo - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- n - Variable in class moa.classifiers.rules.functions.TargetMean
-
- N - Variable in class moa.cluster.CFCluster
-
Number of points in the cluster.
- n_max - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- n_min - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- NaiveBayes - Class in moa.classifiers.bayes
-
Naive Bayes incremental learner.
- NaiveBayes() - Constructor for class moa.classifiers.bayes.NaiveBayes
-
- naiveBayesError - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNodeNBKirkby
-
- naiveBayesError - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNodeWeightedVote
-
- naiveBayesError - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNBAdaptive
-
- naiveBayesError - Variable in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNodeNBKirkby
-
- naiveBayesLimit - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNodeNB
-
- naiveBayesLimit - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- NaiveBayesMultinomial - Class in moa.classifiers.bayes
-
Class for building and using a multinomial Naive
Bayes classifier.
- NaiveBayesMultinomial() - Constructor for class moa.classifiers.bayes.NaiveBayesMultinomial
-
- name - Variable in class com.github.javacliparser.AbstractOption
-
Name of this option.
- name - Variable in class com.yahoo.labs.samoa.instances.Attribute
-
The name.
- name - Variable in class moa.core.Measurement
-
- name - Variable in class moa.gui.experimentertab.Algorithm
-
The name of the algorithms
- name - Variable in class moa.gui.experimentertab.Stream
-
The name of the stream
- name() - Method in class com.yahoo.labs.samoa.instances.Attribute
-
Name.
- nameIsLegal(String) - Static method in class com.github.javacliparser.AbstractOption
-
Gets whether the name is valid or not.
- nameSuffix - Variable in class moa.tasks.meta.MetaMainTask
-
- nanoTimeToSeconds(long) - Static method in class moa.core.TimingUtils
-
- nanSubstitute - Variable in class moa.tasks.FeatureImportanceConfig
-
- nAttributes - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- nbCorrectWeight - Variable in class moa.classifiers.trees.AdaHoeffdingOptionTree.AdaLearningNode
-
- nbCorrectWeight - Variable in class moa.classifiers.trees.ARFHoeffdingTree.LearningNodeNBAdaptive
-
- nbCorrectWeight - Variable in class moa.classifiers.trees.EFDT.LearningNodeNBAdaptive
-
- nbCorrectWeight - Variable in class moa.classifiers.trees.HoeffdingOptionTree.LearningNodeNBAdaptive
-
- nbCorrectWeight - Variable in class moa.classifiers.trees.HoeffdingTree.LearningNodeNBAdaptive
-
- nbCorrectWeight - Variable in class moa.classifiers.trees.LimAttHoeffdingTree.LearningNodeNBAdaptive
-
- nbCorrectWeight - Variable in class moa.classifiers.trees.RandomHoeffdingTree.LearningNodeNBAdaptive
-
- nbInstances - Variable in class moa.classifiers.meta.DACC
-
Number of instances from the stream
- nbThresholdOption - Variable in class moa.classifiers.rules.RuleClassifierNBayes
-
- nbThresholdOption - Variable in class moa.classifiers.trees.EFDT
-
- nbThresholdOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- nbThresholdOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- nearestChild(double[]) - Method in class moa.clusterers.kmeanspm.ClusteringTreeHeadNode
-
- nearestChild(double[]) - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Searches for the nearest child node by comparing each representation.
- nearestEntry(ClusKernel) - Method in class moa.clusterers.clustree.Node
-
Returns the neareast Entry to the given Cluster.
- nearestEntry(Entry) - Method in class moa.clusterers.clustree.Node
-
Return the nearest entry to the given one.
- nearestNeighbour(Instance) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns the nearest neighbour of the supplied target
instance.
- nearestNeighbour(Instance) - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch
-
Returns the nearest instance in the current neighbourhood to the supplied
instance.
- nearestNeighbour(Instance) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Returns the nearest instance in the current neighbourhood to the supplied
instance.
- NearestNeighbourDescription - Class in moa.classifiers.oneclass
-
Implements David Tax's Nearest Neighbour Description method described in
Section 3.4.2 of D.
- NearestNeighbourDescription() - Constructor for class moa.classifiers.oneclass.NearestNeighbourDescription
-
- NearestNeighbourDescription(List<Instance>) - Constructor for class moa.classifiers.oneclass.NearestNeighbourDescription
-
Constructor for a Nearest Neighbour Description classifier based on an argument
training set of instances.
- NearestNeighbourSearch - Class in moa.classifiers.lazy.neighboursearch
-
Abstract class for nearest neighbour search.
- NearestNeighbourSearch() - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Constructor.
- NearestNeighbourSearch(Instances) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Constructor.
- NearestNeighbourSearch.MyHeap - Class in moa.classifiers.lazy.neighboursearch
-
A class for a heap to store the nearest k neighbours to an instance.
- NearestNeighbourSearch.MyHeapElement - Class in moa.classifiers.lazy.neighboursearch
-
A class for storing data about a neighboring instance.
- NearestNeighbourSearch.NeighborList - Class in moa.classifiers.lazy.neighboursearch
-
A class for a linked list to store the nearest k neighbours
to an instance.
- NearestNeighbourSearch.NeighborNode - Class in moa.classifiers.lazy.neighboursearch
-
A class for storing data about a neighboring instance.
- nearestNeighbourSearchOption - Variable in class moa.classifiers.lazy.kNN
-
- negateCondition() - Method in class moa.classifiers.rules.core.conditionaltests.NominalAttributeBinaryRulePredicate
-
- negateCondition() - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- negateCondition() - Method in class moa.classifiers.rules.core.NominalRulePredicate
-
- negateCondition() - Method in class moa.classifiers.rules.core.NumericRulePredicate
-
- negateCondition() - Method in interface moa.classifiers.rules.core.Predicate
-
- negLambda - Variable in class moa.clusterers.clustree.ClusTree
-
Parameter for the weighting function use to weight the entries.
- NeighborList(int) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
Creates the neighborlist with a desired length.
- NeighborNode(double, Instance) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborNode
-
Create a new neighbor node that doesn't link to any other nodes.
- NeighborNode(double, Instance, NearestNeighbourSearch.NeighborNode) - Constructor for class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborNode
-
Create a new neighbor node.
- neighbors - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- neighborsOption - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- neighbourhoodSizeOption - Variable in class moa.classifiers.oneclass.NearestNeighbourDescription
-
- nemenyiTest() - Method in class moa.gui.experimentertab.statisticaltests.StatisticalTest
-
Return the p-values computed by the Nemenyi test.
- nError - Variable in class moa.classifiers.rules.functions.TargetMean
-
- nError - Variable in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- nEstimacion - Variable in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- nEstimators - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- nEstimators - Variable in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- nEstimators - Variable in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- nEstimators - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- nEstimators - Variable in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- nEstimators - Variable in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- newclassifier - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- newClassifierReset - Variable in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- newDefaultRule() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelClassifier
-
- newDefaultRule() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- newDefaultRule() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- newDefaultRule() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiTargetRegressor
-
- newDefaultRule() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiTargetRegressorSemiSuper
-
- newDeletedTree() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- newDeletedTree() - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- newDenseInstance(int) - Method in class com.yahoo.labs.samoa.instances.ArffLoader
-
- newDenseInstance(int) - Method in class com.yahoo.labs.samoa.instances.MultiTargetArffLoader
-
- newErrorWeightedVote() - Method in class moa.classifiers.rules.AbstractAMRules
-
- newErrorWeightedVote() - Method in class moa.classifiers.rules.AMRulesRegressorOld
-
- newErrorWeightedVote() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- newErrorWeightedVote() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- newErrorWeightedVote() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiTargetRegressor
-
- newEstimator() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- newEstimator() - Method in class moa.evaluation.AdwinClassificationPerformanceEvaluator
-
- newEstimator() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- newEstimator() - Method in class moa.evaluation.EWMAClassificationPerformanceEvaluator
-
- newEstimator() - Method in class moa.evaluation.FadingFactorClassificationPerformanceEvaluator
-
- newEstimator() - Method in class moa.evaluation.WindowClassificationPerformanceEvaluator
-
- newHeader - Variable in class moa.streams.IrrelevantFeatureAppenderStream
-
The header with the new features appended.
- newLeafModel() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- newLeafModel() - Method in class moa.classifiers.trees.ARFFIMTDD
-
- newLeafModel() - Method in class moa.classifiers.trees.FIMTDD
-
- newLeafNode() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- newLeafNode() - Method in class moa.classifiers.trees.ARFFIMTDD
-
- newLeafNode() - Method in class moa.classifiers.trees.FIMTDD
-
- newLeafNode(Iadem2.Node, long, long, double[], Instance) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- newLeafNode(Iadem2.Node, long, long, double[], Instance) - Method in class moa.classifiers.trees.iadem.Iadem3
-
- newLearningNode() - Method in class moa.classifiers.trees.EFDT
-
- newLearningNode() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- newLearningNode() - Method in class moa.classifiers.trees.HoeffdingTree
-
- newLearningNode(double[]) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
-
- newLearningNode(double[]) - Method in class moa.classifiers.trees.AdaHoeffdingOptionTree
-
- newLearningNode(double[]) - Method in class moa.classifiers.trees.ARFHoeffdingTree
-
- newLearningNode(double[]) - Method in class moa.classifiers.trees.EFDT
-
- newLearningNode(double[]) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
-
- newLearningNode(double[]) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTreeClassifLeaves
-
- newLearningNode(double[]) - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- newLearningNode(double[]) - Method in class moa.classifiers.trees.HoeffdingTree
-
- newLearningNode(double[]) - Method in class moa.classifiers.trees.HoeffdingTreeClassifLeaves
-
- newLearningNode(double[]) - Method in class moa.classifiers.trees.LimAttHoeffdingTree
-
- newLearningNode(double[]) - Method in class moa.classifiers.trees.RandomHoeffdingTree
-
- newLearningNode(double[], Classifier) - Method in class moa.classifiers.multilabel.MultilabelHoeffdingTree
-
- newLearningNode(double[], Classifier) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTreeClassifLeaves
-
- newLearningNode(double[], Classifier) - Method in class moa.classifiers.trees.HoeffdingTreeClassifLeaves
-
- newline - Static variable in class com.github.javacliparser.StringUtils
-
- newline - Static variable in class moa.core.StringUtils
-
- newNominalClassObserver() - Method in class moa.classifiers.bayes.NaiveBayes
-
- newNominalClassObserver() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- newNominalClassObserver() - Method in class moa.classifiers.rules.RuleClassifier
-
- newNominalClassObserver() - Method in class moa.classifiers.trees.DecisionStump
-
- newNominalClassObserver() - Method in class moa.classifiers.trees.EFDT
-
- newNominalClassObserver() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- newNominalClassObserver() - Method in class moa.classifiers.trees.HoeffdingTree
-
- newNumericClassObserver() - Method in class moa.classifiers.bayes.NaiveBayes
-
- newNumericClassObserver() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- newNumericClassObserver() - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- newNumericClassObserver() - Method in class moa.classifiers.rules.RuleClassifier
-
- newNumericClassObserver() - Method in class moa.classifiers.trees.ARFFIMTDD
-
- newNumericClassObserver() - Method in class moa.classifiers.trees.DecisionStump
-
- newNumericClassObserver() - Method in class moa.classifiers.trees.EFDT
-
- newNumericClassObserver() - Method in class moa.classifiers.trees.FIMTDD
-
- newNumericClassObserver() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- newNumericClassObserver() - Method in class moa.classifiers.trees.HoeffdingTree
-
- newNumericClassObserver() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- newNumericClassObserver() - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- newNumericClassObserver2() - Method in class moa.classifiers.rules.RuleClassifier
-
- newOptionNode() - Method in class moa.classifiers.trees.ORTO
-
- newRule(int, RuleActiveLearningNode, double[]) - Method in class moa.classifiers.rules.AbstractAMRules
-
Rule.Builder() to build an object with the parameters.
- newRule(int, RuleActiveLearningNode, double[]) - Method in class moa.classifiers.rules.AMRulesRegressorOld
-
- newRuleActiveLearningNode(double[]) - Method in class moa.classifiers.rules.AbstractAMRules
-
- newRuleActiveLearningNode(double[]) - Method in class moa.classifiers.rules.AMRulesRegressorOld
-
- newRuleActiveLearningNode(Rule.Builder) - Method in class moa.classifiers.rules.AbstractAMRules
-
- newRuleActiveLearningNode(Rule.Builder) - Method in class moa.classifiers.rules.AMRulesRegressorOld
-
- newSparseInstance(double) - Method in class com.yahoo.labs.samoa.instances.ArffLoader
-
- newSparseInstance(double, double[]) - Method in class com.yahoo.labs.samoa.instances.ArffLoader
-
- newSparseInstance(double, double[]) - Method in class com.yahoo.labs.samoa.instances.MultiTargetArffLoader
-
- newSplit(int) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- newSplit(int) - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- newSplitNode(InstanceConditionalTest) - Method in class moa.classifiers.trees.ARFFIMTDD
-
- newSplitNode(InstanceConditionalTest) - Method in class moa.classifiers.trees.FIMTDD
-
- newSplitNode(InstanceConditionalTest, double[]) - Method in class moa.classifiers.trees.EFDT
-
- newSplitNode(InstanceConditionalTest, double[]) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
-
- newSplitNode(InstanceConditionalTest, double[]) - Method in class moa.classifiers.trees.HoeffdingTree
-
- newSplitNode(InstanceConditionalTest, double[], int) - Method in class moa.classifiers.trees.EFDT
-
- newSplitNode(InstanceConditionalTest, double[], int) - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree
-
- newSplitNode(InstanceConditionalTest, double[], int) - Method in class moa.classifiers.trees.HoeffdingTree
-
- newSplitNode(Predicate) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- newThreshold - Variable in class moa.classifiers.active.ALUncertainty
-
- newTreeChange() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- newTreeChange() - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- next() - Method in interface moa.recommender.dataset.Dataset
-
- next() - Method in class moa.recommender.dataset.impl.FlixsterDataset
-
- next() - Method in class moa.recommender.dataset.impl.JesterDataset
-
- next() - Method in class moa.recommender.dataset.impl.MovielensDataset
-
- next() - Method in class moa.recommender.rc.data.impl.MemRecommenderData.RatingIterator
-
- next() - Method in class moa.recommender.rc.utils.DenseVector.DenseVectorIterator
-
- next() - Method in class moa.recommender.rc.utils.SparseVector.SparseVectorIterator
-
- next(int) - Method in class moa.clusterers.streamkm.MTRandom
-
This method forms the basis for generating a pseudo random number
sequence from this class.
- nextClassShouldBeZero - Variable in class moa.streams.generators.AgrawalGenerator
-
- nextClassShouldBeZero - Variable in class moa.streams.generators.AssetNegotiationGenerator
-
- nextClassShouldBeZero - Variable in class moa.streams.generators.MixedGenerator
-
- nextClassShouldBeZero - Variable in class moa.streams.generators.SEAGenerator
-
- nextClassShouldBeZero - Variable in class moa.streams.generators.SineGenerator
-
- nextClassShouldBeZero - Variable in class moa.streams.generators.STAGGERGenerator
-
- nextHashFunction() - Method in class moa.clusterers.kmeanspm.DietzfelbingerHash
-
Generates a new Dietzfelbinger hash function.
- nextInstance() - Method in class moa.streams.ArffFileStream
-
- nextInstance() - Method in class moa.streams.BootstrappedStream
-
- nextInstance() - Method in class moa.streams.CachedInstancesStream
-
- nextInstance() - Method in class moa.streams.clustering.FileStream
-
- nextInstance() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- nextInstance() - Method in class moa.streams.clustering.SimpleCSVStream
-
- nextInstance() - Method in class moa.streams.ConceptDriftRealStream
-
- nextInstance() - Method in class moa.streams.ConceptDriftStream
-
- nextInstance() - Method in interface moa.streams.ExampleStream
-
Gets the next example from this stream.
- nextInstance() - Method in class moa.streams.FilteredStream
-
- nextInstance() - Method in class moa.streams.filters.AbstractStreamFilter
-
- nextInstance() - Method in class moa.streams.filters.RBFFilter
-
- nextInstance() - Method in class moa.streams.filters.RemoveDiscreteAttributeFilter
-
- nextInstance() - Method in class moa.streams.filters.ReplacingMissingValuesFilter
-
- nextInstance() - Method in class moa.streams.filters.SelectAttributesFilter
-
- nextInstance() - Method in class moa.streams.generators.AgrawalGenerator
-
- nextInstance() - Method in class moa.streams.generators.AssetNegotiationGenerator
-
- nextInstance() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- nextInstance() - Method in class moa.streams.generators.HyperplaneGenerator
-
- nextInstance() - Method in class moa.streams.generators.LEDGenerator
-
- nextInstance() - Method in class moa.streams.generators.LEDGeneratorDrift
-
- nextInstance() - Method in class moa.streams.generators.MixedGenerator
-
- nextInstance() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
GenerateML.
- nextInstance() - Method in class moa.streams.generators.RandomRBFGenerator
-
- nextInstance() - Method in class moa.streams.generators.RandomRBFGeneratorDrift
-
- nextInstance() - Method in class moa.streams.generators.RandomTreeGenerator
-
- nextInstance() - Method in class moa.streams.generators.SEAGenerator
-
- nextInstance() - Method in class moa.streams.generators.SineGenerator
-
- nextInstance() - Method in class moa.streams.generators.STAGGERGenerator
-
- nextInstance() - Method in class moa.streams.generators.TextGenerator
-
- nextInstance() - Method in class moa.streams.generators.WaveformGenerator
-
- nextInstance() - Method in class moa.streams.generators.WaveformGeneratorDrift
-
- nextInstance() - Method in class moa.streams.ImbalancedStream
-
- nextInstance() - Method in class moa.streams.IrrelevantFeatureAppenderStream
-
- nextInstance() - Method in class moa.streams.MultiFilteredStream
-
- nextInstance() - Method in class moa.streams.MultiLabelFilteredStream
-
- nextInstance() - Method in class moa.streams.MultiTargetArffFileStream
-
- nextInstance() - Method in class moa.streams.PartitioningStream
-
- nextInstance() - Method in class moa.streams.RecurrentConceptDriftStream
-
- nextOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- nextValue() - Method in class moa.streams.generators.cd.AbruptChangeGenerator
-
- nextValue() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- nextValue() - Method in class moa.streams.generators.cd.GradualChangeGenerator
-
- nextValue() - Method in class moa.streams.generators.cd.NoChangeGenerator
-
- nFeatures - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- nGeneratedMajorityTotal - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- nGeneratedMajorityTotal - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- nGeneratedMinorityTotal - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- nGeneratedMinorityTotal - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- nInlier - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
-
- nInlier - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
-
- nInlier - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- nInlier - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- nItems - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
-
- nIterations - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- nMajorityTotal - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- nMajorityTotal - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- nMinorityTotal - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- nMinorityTotal - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- nNegative - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- NO_SOURCE - Static variable in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Message shown when no instances have been loaded and no attribute set
- NO_SOURCE - Static variable in class moa.gui.featureanalysis.InstancesSummaryPanel
-
Message shown when no instances have been loaded
- NoAnomalyDetection - Class in moa.classifiers.rules.core.anomalydetection
-
No anomaly detection is performed
- NoAnomalyDetection() - Constructor for class moa.classifiers.rules.core.anomalydetection.NoAnomalyDetection
-
- noAnomalyDetectionOption - Variable in class moa.classifiers.rules.AbstractAMRules
-
- NOBOX_HORIZONTAL - moa.gui.experimentertab.PlotTab.LegendType
-
- NOBOX_HORIZONTAL - moa.tasks.Plot.LegendType
-
- NOBOX_VERTICAL - moa.gui.experimentertab.PlotTab.LegendType
-
- NOBOX_VERTICAL - moa.tasks.Plot.LegendType
-
- NoChange - Class in moa.classifiers.functions
-
NoChange class classifier.
- NoChange() - Constructor for class moa.classifiers.functions.NoChange
-
- NoChangeDetection - Class in moa.classifiers.rules.core.changedetection
-
- NoChangeDetection() - Constructor for class moa.classifiers.rules.core.changedetection.NoChangeDetection
-
- NoChangeGenerator - Class in moa.streams.generators.cd
-
- NoChangeGenerator() - Constructor for class moa.streams.generators.cd.NoChangeGenerator
-
- node - Variable in class moa.classifiers.trees.EFDT.FoundNode
-
- node - Variable in class moa.classifiers.trees.HoeffdingOptionTree.FoundNode
-
- node - Variable in class moa.classifiers.trees.HoeffdingTree.FoundNode
-
- node - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBSearchResult
-
- node - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBSearchResult
-
- node - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBSearchResult
-
- node - Variable in class moa.clusterers.outliers.MCOD.MCODBase.EventItem
-
- node - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBSearchResult
-
- node - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventItem
-
- Node - Class in moa.clusterers.clustree
-
- Node() - Constructor for class moa.streams.generators.RandomTreeGenerator.Node
-
- Node(double[]) - Constructor for class moa.classifiers.trees.EFDT.Node
-
- Node(double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.Node
-
- Node(double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.Node
-
- Node(double, double) - Constructor for class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
-
- Node(double, double, double) - Constructor for class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
-
- Node(double, double, double) - Constructor for class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver.Node
-
- Node(double, int, double) - Constructor for class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
-
- Node(double, DoubleVector[]) - Constructor for class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree.Node
-
- Node(double, DoubleVector[]) - Constructor for class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat.Node
-
- Node(float, SingleVector[]) - Constructor for class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat.Node
-
- Node(int, int) - Constructor for class moa.clusterers.clustree.Node
-
Initialze a normal node, which is not fake.
- Node(int, int, int, boolean) - Constructor for class moa.clusterers.clustree.Node
-
Initialiazes a node which is a fake root depending on the given
boolean.
- Node(int, int, Entry[]) - Constructor for class moa.clusterers.clustree.Node
-
USED FOR EM_TOP_DOWN BULK LOADING
- Node(ISOUPTree) - Constructor for class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- Node(ARFFIMTDD) - Constructor for class moa.classifiers.trees.ARFFIMTDD.Node
-
- Node(FIMTDD) - Constructor for class moa.classifiers.trees.FIMTDD.Node
-
- Node(Iadem2, Iadem2.Node, double[]) - Constructor for class moa.classifiers.trees.iadem.Iadem2.Node
-
- nodeCountAtLastFeatureImportanceInquiry - Variable in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTree
-
- nodeList - Variable in class moa.classifiers.rules.core.Rule
-
- nodes - Variable in class moa.clusterers.outliers.MCOD.MicroCluster
-
- nodeSplitterTipText() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Returns the tip text for this property.
- nodesReinsert - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- nodeStatistics - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- nodeTime - Variable in class moa.classifiers.trees.EFDT.Node
-
- nodeType - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- nodo - Variable in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- NoFeatureRanking - Class in moa.classifiers.rules.featureranking
-
No feature ranking is performed
- NoFeatureRanking() - Constructor for class moa.classifiers.rules.featureranking.NoFeatureRanking
-
- NoInstanceTransformation - Class in moa.classifiers.rules.multilabel.instancetransformers
-
Performs no transformation.
- NoInstanceTransformation() - Constructor for class moa.classifiers.rules.multilabel.instancetransformers.NoInstanceTransformation
-
- noiseInClusterOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- noiseLabel - Variable in class moa.gui.visualization.DataPoint
-
- noiseLevelOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- noisePercentage - Variable in class moa.streams.generators.AssetNegotiationGenerator
-
- noisePercentageOption - Variable in class moa.streams.generators.HyperplaneGenerator
-
- noisePercentageOption - Variable in class moa.streams.generators.LEDGenerator
-
- noisePercentageOption - Variable in class moa.streams.generators.SEAGenerator
-
- nominalAttClassObserver - Variable in class moa.classifiers.trees.iadem.Iadem2.NominalVirtualNode
-
- NominalAttributeBinaryRulePredicate - Class in moa.classifiers.rules.core.conditionaltests
-
Nominal binary conditional test for instances to use to split nodes in rules.
- NominalAttributeBinaryRulePredicate(int, int) - Constructor for class moa.classifiers.rules.core.conditionaltests.NominalAttributeBinaryRulePredicate
-
- NominalAttributeBinaryTest - Class in moa.classifiers.core.conditionaltests
-
Nominal binary conditional test for instances to use to split nodes in Hoeffding trees.
- NominalAttributeBinaryTest(int, int) - Constructor for class moa.classifiers.core.conditionaltests.NominalAttributeBinaryTest
-
- NominalAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers
-
Class for observing the class data distribution for a nominal attribute.
- NominalAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
-
- NominalAttributeMultiwayTest - Class in moa.classifiers.core.conditionaltests
-
Nominal multi way conditional test for instances to use to split nodes in Hoeffding trees.
- NominalAttributeMultiwayTest(int) - Constructor for class moa.classifiers.core.conditionaltests.NominalAttributeMultiwayTest
-
- nominalAttUsed(Instance) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- nominalEstimatorOption - Variable in class moa.classifiers.trees.EFDT
-
- nominalEstimatorOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- nominalEstimatorOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- nominalObserverOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- nominalObserverOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- nominalReplacementStrategyOption - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
-
- NominalRulePredicate - Class in moa.classifiers.rules.core
-
Class that contains the literal information for a nominal variable
- NominalRulePredicate(int, double, boolean) - Constructor for class moa.classifiers.rules.core.NominalRulePredicate
-
- nominalSelectedStrategy - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
-
- nominalStatisticsObserver - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- NominalStatisticsObserver - Interface in moa.classifiers.rules.multilabel.attributeclassobservers
-
- NominalVirtualNode(Iadem2, Iadem2.Node, int, boolean, boolean) - Constructor for class moa.classifiers.trees.iadem.Iadem2.NominalVirtualNode
-
- NON_HANDLER_CAPABILITIES - Static variable in class moa.capabilities.CapabilityRequirement
-
The capabilities to assume a class has if it does not implement
the CapabilitiesHandler interface.
- NonConvexCluster - Class in moa.clusterers.macro
-
- NonConvexCluster(CFCluster, List<CFCluster>) - Constructor for class moa.clusterers.macro.NonConvexCluster
-
- NONE - moa.gui.experimentertab.PlotTab.LegendType
-
- NONE - moa.tasks.Plot.LegendType
-
- noOfKthNearest() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap
-
returns the number of k nearest.
- noPrePruneOption - Variable in class moa.classifiers.trees.EFDT
-
- noPrePruneOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- noPrePruneOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- norm() - Method in class moa.recommender.rc.utils.Vector
-
- norm(double, int) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Normalizes a given value of a numeric attribute.
- NORMAL_CONSTANT - Static variable in class moa.classifiers.rules.AbstractAMRules
-
- NORMAL_CONSTANT - Static variable in class moa.core.GaussianEstimator
-
- normalInverse(double) - Static method in class moa.core.Statistics
-
Returns the value, x, for which the area under the
Normal (Gaussian) probability density function (integrated from
minus infinity to x) is equal to the argument y
(assumes mean is zero, variance is one).
- NormalizableDistance - Class in moa.classifiers.lazy.neighboursearch
-
Represents the abstract ancestor for normalizable distance functions, like
Euclidean or Manhattan distance.
- NormalizableDistance() - Constructor for class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Invalidates the distance function, Instances must be still set.
- NormalizableDistance(Instances) - Constructor for class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Initializes the distance function and automatically initializes the
ranges.
- normalize() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- normalize() - Method in class moa.classifiers.rules.core.voting.Vote
-
- normalize() - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- normalize() - Method in class moa.classifiers.rules.multilabel.core.voting.MultiLabelVote
-
- normalize() - Method in class moa.core.DoubleVector
-
- normalize(double[]) - Static method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- normalize(double[]) - Method in class moa.classifiers.rules.RuleClassifierNBayes
-
- normalize(double[]) - Static method in class moa.core.Utils
-
Normalizes the doubles in the array by their sum.
- normalize(double[], double) - Static method in class moa.core.Utils
-
Normalizes the doubles in the array using the given value.
- normalizedInputVector(MultiLabelInstance) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- normalizedInstance(Instance) - Method in class moa.classifiers.rules.functions.Perceptron
-
- normalizedInstance(Instance) - Method in class moa.classifiers.trees.ARFFIMTDD.FIMTDDPerceptron
-
- normalizedInstance(Instance) - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
-
- normalizedPrediction(Instance) - Method in class moa.classifiers.rules.functions.Perceptron
-
- normalizedTargetVector(MultiLabelInstance) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- normalizeNodeWidthTipText() - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Tip text for this property.
- normalizeOption - Variable in class moa.streams.clustering.FileStream
-
- normalizeTargetValue(double) - Method in class moa.classifiers.trees.ARFFIMTDD
-
- normalizeTargetValue(double) - Method in class moa.classifiers.trees.FIMTDD
-
- normalizeTargetValue(double, int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- normalizeTargetValue(MultiLabelInstance, int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- normalizeTargetVector(double[]) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- normalizeWeights() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.MultitargetPerceptron
-
- normalizeWeights() - Method in class moa.classifiers.rules.functions.Perceptron
-
- normalProbability(double) - Static method in class moa.core.Statistics
-
Returns the area under the Normal (Gaussian) probability density
function, integrated from minus infinity to x
(assumes mean is zero, variance is one).
- normp(double) - Static method in class moa.gui.experimentertab.statisticaltests.CDF_Normal
-
This method calculates the normal cumulative distribution function.
- NOT_STARTED - moa.gui.experimentertab.ExpTaskThread.Status
-
- NOT_STARTED - moa.tasks.TaskThread.Status
-
- notBinaryStreamOption - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- NotebookBuilder - Class in moa.tasks.ipynb
-
Manage the list of all cells
Add new cells
Create a Jupyter NotebookBuilder as IPYNB file
- NotebookBuilder() - Constructor for class moa.tasks.ipynb.NotebookBuilder
-
- NotebookCellBuilder - Class in moa.tasks.ipynb
-
Abstract class of a cell
- notebookOutputFile - Variable in class moa.tasks.WriteConfigurationToJupyterNotebook
-
- notify(ObserverMOAObject, FeatureRankingMessage) - Method in class moa.classifiers.rules.multilabel.core.ObservableMOAObject
-
- notifyAll(FeatureRankingMessage) - Method in class moa.classifiers.rules.multilabel.core.ObservableMOAObject
-
- notifyChangeListeners() - Method in class com.github.javacliparser.gui.ClassOptionEditComponent
-
Notifies all registered change listeners that the options have changed.
- notifyChangeListeners() - Method in class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
Notifies all registered change listeners that the options have changed.
- nOutlier - Variable in class moa.clusterers.outliers.AbstractC.ISBIndex.ISBNode
-
- nOutlier - Variable in class moa.clusterers.outliers.Angiulli.ISBIndex.ISBNode
-
- nOutlier - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- nOutlier - Variable in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- nPositive - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- nr_points() - Method in class moa.cluster.Miniball
-
Return the actual number of points in the list
- nr_support_points() - Method in class moa.cluster.Miniball
-
Return the number of support points (used to calculate the miniball).
It's and internal info
- nRangeQueriesExecuted - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- nRatings - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
-
- nTimePerObj - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- nTotalRunTime - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- NullAttributeClassObserver - Class in moa.classifiers.core.attributeclassobservers
-
Class for observing the class data distribution for a null attribute.
- NullAttributeClassObserver() - Constructor for class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
-
- NullMonitor - Class in moa.tasks
-
Class that represents a null monitor.
- NullMonitor() - Constructor for class moa.tasks.NullMonitor
-
- nullString - Variable in class com.github.javacliparser.AbstractClassOption
-
The null text.
- nullString - Variable in class moa.options.AbstractClassOption
-
The null text.
- NUM_BASE_ATTRIBUTES - Static variable in class moa.streams.generators.WaveformGenerator
-
- NUM_CLASSES - Static variable in class moa.streams.generators.WaveformGenerator
-
- NUM_IRRELEVANT_ATTRIBUTES - Static variable in class moa.streams.generators.LEDGenerator
-
- NUM_IRRELEVANT_ATTRIBUTES - Static variable in class moa.streams.generators.SineGenerator
-
- numAttributes - Variable in class moa.classifiers.meta.RandomRules
-
- numAttributes - Variable in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- numAttributes - Variable in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- numAttributes - Variable in class moa.classifiers.trees.ARFHoeffdingTree.RandomLearningNode
-
- numAttributes - Variable in class moa.classifiers.trees.LimAttHoeffdingTree.LimAttLearningNode
-
- numAttributes - Variable in class moa.classifiers.trees.RandomHoeffdingTree.RandomLearningNode
-
- numAttributes - Variable in class moa.streams.clustering.SimpleCSVStream
-
- numAttributes - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
-
- numAttributes() - Method in class com.yahoo.labs.samoa.instances.DenseInstanceData
-
Num attributes.
- numAttributes() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Gets the number of attributes.
- numAttributes() - Method in interface com.yahoo.labs.samoa.instances.InstanceData
-
Num attributes.
- numAttributes() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Num attributes.
- numAttributes() - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- numAttributes() - Method in class com.yahoo.labs.samoa.instances.Instances
-
Num attributes.
- numAttributes() - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Gets the number of attributes.
- numAttributesOption - Variable in class moa.classifiers.meta.LimAttClassifier
-
- numAttributesPercentageOption - Variable in class moa.classifiers.meta.RandomRules
-
- numAttributesPercentageOption - Variable in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- numAttributesPercentageOption - Variable in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- numAttributesSelected - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- numAttsOption - Variable in class moa.streams.clustering.ClusteringStream
-
- numAttsOption - Variable in class moa.streams.generators.HyperplaneGenerator
-
- numAttsOption - Variable in class moa.streams.generators.RandomRBFGenerator
-
- numAttsOption - Variable in class moa.streams.generators.TextGenerator
-
- numberAttribute - Variable in class moa.streams.generators.LEDGeneratorDrift
-
- numberAttribute - Variable in class moa.streams.generators.WaveformGeneratorDrift
-
- numberAttributes - Variable in class com.yahoo.labs.samoa.instances.AttributesInformation
-
The number of attributes.
- numberAttributes - Variable in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
The number of attributes.
- numberAttributes - Variable in class moa.classifiers.functions.Perceptron
-
- numberAttributes - Variable in class moa.classifiers.meta.LimAttClassifier
-
- numberAttributesDriftOption - Variable in class moa.streams.generators.LEDGeneratorDrift
-
- numberAttributesDriftOption - Variable in class moa.streams.generators.WaveformGeneratorDrift
-
- numberChanges - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- numberClasses - Variable in class moa.classifiers.functions.Perceptron
-
- numberDetections - Variable in class moa.classifiers.functions.Perceptron
-
- numberDetections - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- numberDetectionsOccurred - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- numberInstance - Variable in class moa.streams.generators.HyperplaneGenerator
-
- numberInstances - Variable in class moa.classifiers.meta.WEKAClassifier
-
- numberInstances - Variable in class moa.clusterers.streamkm.StreamKM
-
- numberInstanceStream - Variable in class moa.streams.ConceptDriftRealStream
-
- numberInstanceStream - Variable in class moa.streams.ConceptDriftStream
-
- numberLeaves() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- numberLeaves() - Method in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- numberLeaves() - Method in interface moa.classifiers.trees.HoeffdingAdaptiveTree.NewNode
-
- numberOfBuckets - Variable in class moa.clusterers.streamkm.BucketManager
-
- numberOfCentres - Variable in class moa.clusterers.streamkm.StreamKM
-
- numberOfChangesDetected - Variable in class moa.classifiers.meta.LeveragingBag
-
- numberOfChangesDetected - Variable in class moa.classifiers.meta.LimAttClassifier
-
- numberOfChangesDetected - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- numberOfClusters() - Method in class moa.clusterers.CobWeb
-
Returns the number of clusters.
- numberOfDriftsDetected - Variable in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- numberOfDriftsDetected - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- numberOfDriftsDetected - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- numberOfDriftsInduced - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- numberOfErrors - Variable in class moa.classifiers.meta.PairedLearners
-
- numberOfInstancesProcessed - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- numberOfJobsOption - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- numberOfLeaves - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- numberOfNodes - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- numberOfSamples - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
-
- numberOfWarningsDetected - Variable in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- numberOfWarningsDetected - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- numberOfWarningsDetected - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- numberOfWarningsInduced - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- numberOutputs - Variable in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- numberOutputs - Variable in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- numberOutputs - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- numberOutputs - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- numberOutputTargets() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Gets the number of output attributes.
- numberOutputTargets() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- numberTotalExamples - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- numberWarnings - Variable in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- numBinsOption - Variable in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- numBinsOption - Variable in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
-
- numBytesWritten - Variable in class com.github.javacliparser.SerializeUtils.ByteCountingOutputStream
-
- numBytesWritten - Variable in class moa.core.SerializeUtils.ByteCountingOutputStream
-
- numCategoricalFeaturesOption - Variable in class moa.streams.IrrelevantFeatureAppenderStream
-
- numCentroidsOption - Variable in class moa.streams.generators.RandomRBFGenerator
-
- numChildren() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- numChildren() - Method in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- numChildren() - Method in class moa.classifiers.trees.EFDT.SplitNode
-
- numChildren() - Method in class moa.classifiers.trees.FIMTDD.InnerNode
-
- numChildren() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- numChildren() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- numClasses - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator
-
- numClasses - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- numClasses - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- numClasses - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- numClasses - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator
-
- numClasses - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- numClasses - Variable in class moa.streams.ImbalancedStream
-
- numClasses() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Num classes.
- numClasses() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Num classes.
- numClasses() - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- numClasses() - Method in class com.yahoo.labs.samoa.instances.Instances
-
Num classes.
- numClasses(int) - Method in class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- numClasses(int) - Method in interface com.yahoo.labs.samoa.instances.Prediction
-
Different output attributes may have different number of classes.
- numClassesOption - Variable in class moa.streams.generators.HyperplaneGenerator
-
- numClassesOption - Variable in class moa.streams.generators.RandomRBFGenerator
-
- numClassesOption - Variable in class moa.streams.generators.RandomTreeGenerator
-
- numClusterOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- numClusterRangeOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- numClusters - Variable in class moa.clusterers.kmeanspm.BICO
-
- numClustersOption - Variable in class moa.clusterers.kmeanspm.BICO
-
- numClustersOption - Variable in class moa.clusterers.streamkm.StreamKM
-
- numDeletedTrees() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- numDimensions - Variable in class moa.clusterers.kmeanspm.BICO
-
- numDimensionsOption - Variable in class moa.clusterers.kmeanspm.BICO
-
- numDriftAttsOption - Variable in class moa.streams.generators.HyperplaneGenerator
-
- numDriftCentroidsOption - Variable in class moa.streams.generators.RandomRBFGeneratorDrift
-
- numEnsemblePruningOption - Variable in class moa.classifiers.meta.LimAttClassifier
-
- numEntries() - Method in class moa.evaluation.preview.LearningCurve
-
- numEntries() - Method in class moa.evaluation.preview.Preview
-
- numEntries() - Method in class moa.evaluation.preview.PreviewCollection
-
- numEntries() - Method in class moa.evaluation.preview.PreviewCollectionLearningCurveWrapper
-
- numEntries() - Method in class moa.streams.filters.Selection
-
- numericalConstantValueOption - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
-
- NumericalParameter - Class in moa.clusterers.meta
-
- NumericalParameter(NumericalParameter) - Constructor for class moa.clusterers.meta.NumericalParameter
-
- NumericalParameter(ParameterConfiguration) - Constructor for class moa.clusterers.meta.NumericalParameter
-
- numericalSelectedStrategy - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
-
- numericAttClassObserver - Variable in class moa.classifiers.trees.iadem.Iadem2.NumericVirtualNode
-
- NumericAttributeBinaryRulePredicate - Class in moa.classifiers.rules.core.conditionaltests
-
Numeric binary conditional test for instances to use to split nodes in
AMRules.
- NumericAttributeBinaryRulePredicate(int, double, int) - Constructor for class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- NumericAttributeBinaryTest - Class in moa.classifiers.core.conditionaltests
-
Numeric binary conditional test for instances to use to split nodes in Hoeffding trees.
- NumericAttributeBinaryTest(int, double, boolean) - Constructor for class moa.classifiers.core.conditionaltests.NumericAttributeBinaryTest
-
- NumericAttributeClassObserver - Interface in moa.classifiers.core.attributeclassobservers
-
Interface for observing the class data distribution for a numeric attribute.
- numericAttributes - Variable in class moa.streams.filters.RemoveDiscreteAttributeFilter
-
- numericAttributesIndex - Variable in class moa.classifiers.rules.functions.Perceptron
-
- numericEstimatorOption - Variable in class moa.classifiers.trees.EFDT
-
- numericEstimatorOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- numericEstimatorOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- numericEstimatorOption - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- numericObserverOption - Variable in class moa.classifiers.rules.AbstractAMRules
-
- numericObserverOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- numericObserverOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- numericReplacementStrategyOption - Variable in class moa.streams.filters.ReplacingMissingValuesFilter
-
- NumericRulePredicate - Class in moa.classifiers.rules.core
-
Class that contains the literal information for a numerical variable
- NumericRulePredicate(int, double, boolean) - Constructor for class moa.classifiers.rules.core.NumericRulePredicate
-
- numericStatisticsObserver - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- NumericStatisticsObserver - Interface in moa.classifiers.rules.multilabel.attributeclassobservers
-
- NumericVirtualNode(Iadem2, Iadem2.Node, int, IademNumericAttributeObserver) - Constructor for class moa.classifiers.trees.iadem.Iadem2.NumericVirtualNode
-
- numFolds - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- numFoldsOption - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Number of folds in candidate classifier cross-validation.
- numFoldsOption - Variable in class moa.tasks.EvaluatePrequentialCV
-
- numFoldsOption - Variable in class moa.tasks.EvaluatePrequentialDelayedCV
-
- numFreeEntries() - Method in class moa.clusterers.clustree.Node
-
Return the number of free Entrys in this node.
- numInitPoints - Variable in class moa.clusterers.denstream.WithDBSCAN
-
- numInputAttributes() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Gets the number of input attributes.
- numInputAttributes() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- numInputAttributes() - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- numInputAttributes() - Method in class com.yahoo.labs.samoa.instances.InstancesHeader
-
- numInstances - Variable in class moa.classifiers.meta.LimAttClassifier
-
- numInstances - Variable in class moa.classifiers.trees.EFDT
-
- numInstances - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- numInstances() - Method in class com.yahoo.labs.samoa.instances.Instances
-
Num instances.
- numInstances() - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNode
-
Returns the number of Instances
in the rectangular region defined
by this node.
- numInstancesConcept - Variable in class moa.streams.generators.SEAGenerator
-
- numInstancesConceptOption - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- numInstancesInitOption - Variable in class moa.classifiers.active.ALUncertainty
-
- numInstancesRead - Variable in class moa.streams.ArffFileStream
-
- numInstancesRead - Variable in class moa.streams.clustering.FileStream
-
- numInstancesRead - Variable in class moa.streams.clustering.SimpleCSVStream
-
- numInstancesRead - Variable in class moa.streams.MultiTargetArffFileStream
-
- numLabelsOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- numLabelsOption - Variable in class moa.streams.generators.multilabel.MultilabelArffFileStream
-
- numLatentOption - Variable in class moa.streams.filters.RBFFilter
-
- numLatentOption - Variable in class moa.streams.filters.ReLUFilter
-
- numLearnedOutputs - Variable in class moa.classifiers.rules.multilabel.errormeasurers.MeanAbsoluteDeviationMT
-
- numLearnedOutputs - Variable in class moa.classifiers.rules.multilabel.errormeasurers.RelativeMeanAbsoluteDeviationMT
-
- numLearnedOutputs - Variable in class moa.classifiers.rules.multilabel.errormeasurers.RelativeRootMeanSquaredErrorMT
-
- numLearnedOutputs - Variable in class moa.classifiers.rules.multilabel.errormeasurers.RootMeanSquaredErrorMT
-
- numNeg - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- numNeg - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- numNodes - Variable in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver
-
- numNodes - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- numNodes - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- numNominalsOption - Variable in class moa.streams.generators.RandomTreeGenerator
-
- numNonZeroEntries() - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- numNonZeroEntries() - Method in class moa.core.DoubleVector
-
- numNumericFeaturesOption - Variable in class moa.streams.IrrelevantFeatureAppenderStream
-
- numNumericsOption - Variable in class moa.streams.generators.RandomTreeGenerator
-
- numObservations - Variable in class moa.core.GreenwaldKhannaQuantileSummary
-
- numOldLabelsOption - Variable in class moa.classifiers.meta.TemporallyAugmentedClassifier
-
- numOptions() - Method in class com.github.javacliparser.Options
-
- numOutputAttributes() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Gets the number of output attributes.
- numOutputAttributes() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- numOutputAttributes() - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- numOutputAttributes() - Method in class com.yahoo.labs.samoa.instances.InstancesHeader
-
- numOutputAttributes() - Method in class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- numOutputAttributes() - Method in interface com.yahoo.labs.samoa.instances.Prediction
-
Number of output attributes.
- numPartitions - Variable in class moa.streams.PartitioningStream
-
- numPartitionsOption - Variable in class moa.streams.PartitioningStream
-
- numPartitionsOption - Variable in class moa.tasks.meta.ALPartitionEvaluationTask
-
- numPassesOption - Variable in class moa.tasks.LearnModel
-
- numPassesOption - Variable in class moa.tasks.LearnModelMultiLabel
-
- numPassesOption - Variable in class moa.tasks.LearnModelMultiTarget
-
- numPassesOption - Variable in class moa.tasks.LearnModelRegression
-
- numPos - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- numPos - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- numProcessedPerUnit - Variable in class moa.clusterers.denstream.WithDBSCAN
-
- numProjections - Variable in class moa.clusterers.kmeanspm.BICO
-
- numProjectionsOption - Variable in class moa.clusterers.kmeanspm.BICO
-
- numRepOption - Variable in class moa.streams.RecurrentConceptDriftStream
-
- numSourceInstancesOutputs - Variable in class moa.classifiers.rules.multilabel.instancetransformers.InstanceAttributesSelector
-
- numSourceInstancesOutputs - Variable in class moa.classifiers.rules.multilabel.instancetransformers.InstanceOutputAttributesSelector
-
- numSplits() - Method in class moa.classifiers.core.AttributeSplitSuggestion
-
- numSplitsByBreakingTies - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- numStreamsOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- numStreamsOption - Variable in class moa.tasks.WriteMultipleStreamsToARFF
-
- numSubsetsGreaterThanFrac(double[][], double) - Static method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
-
- numSubtrees() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- numTokens - Variable in class moa.streams.clustering.SimpleCSVStream
-
- numTrees - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- numTrees() - Method in class moa.classifiers.trees.iadem.Iadem3
-
- numTreesOption - Variable in class moa.classifiers.oneclass.HSTrees
-
- numTuples - Variable in class moa.core.GreenwaldKhannaQuantileSummary
-
- numTuplesOption - Variable in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
-
- numValsPerNominalOption - Variable in class moa.streams.generators.RandomTreeGenerator
-
- numValues() - Method in class com.yahoo.labs.samoa.instances.Attribute
-
Num values.
- numValues() - Method in class com.yahoo.labs.samoa.instances.DenseInstanceData
-
Num values.
- numValues() - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Gets the number of values, mainly for sparse instances.
- numValues() - Method in interface com.yahoo.labs.samoa.instances.InstanceData
-
Num values.
- numValues() - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Num values.
- numValues() - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Num values.
- numValues() - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- numValues() - Method in class moa.core.DoubleVector
-
- numValues() - Method in class moa.streams.filters.Selection
-
- numValuesCategoricalFeatureOption - Variable in class moa.streams.IrrelevantFeatureAppenderStream
-
- nUsers - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
-
- p - Variable in class moa.classifiers.rules.functions.AdaptiveNodePredictor
-
- p - Variable in class moa.evaluation.CMM_GTAnalysis.CMMPoint
-
Reference to original point
- P0 - Static variable in class moa.core.Statistics
-
COEFFICIENTS FOR METHOD normalInverse() *
- P1 - Static variable in class moa.core.Statistics
-
- p1evl(double, double[], int) - Static method in class moa.core.Statistics
-
Evaluates the given polynomial of degree N at x.
- P2 - Static variable in class moa.core.Statistics
-
- pack(byte[]) - Static method in class moa.clusterers.streamkm.MTRandom
-
This simply utility method can be used in cases where a byte
array of seed data is to be used to repeatedly re-seed the
random number sequence.
- padLeft(String, int) - Static method in class moa.core.Utils
-
Pads a string to a specified length, inserting spaces on the left
as required.
- padRight(String, int) - Static method in class moa.core.Utils
-
Pads a string to a specified length, inserting spaces on the right
as required.
- pageHinckleyAlphaOption - Variable in class moa.classifiers.rules.AbstractAMRules
-
- PageHinckleyAlphaOption - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- PageHinckleyAlphaOption - Variable in class moa.classifiers.trees.FIMTDD
-
- pageHinckleyTest - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- PageHinckleyTest(double, double) - Method in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
Check to see if the tree needs updating
- PageHinckleyTest(double, double) - Method in class moa.classifiers.trees.FIMTDD.InnerNode
-
Check to see if the tree needs updating
- PageHinckleyTest(double, double, int) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
Check to see if the tree needs updating
- pageHinckleyThresholdOption - Variable in class moa.classifiers.rules.AbstractAMRules
-
- PageHinckleyThresholdOption - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- PageHinckleyThresholdOption - Variable in class moa.classifiers.trees.FIMTDD
-
- PageHinkleyDM - Class in moa.classifiers.core.driftdetection
-
Drift detection method based in Page Hinkley Test.
- PageHinkleyDM() - Constructor for class moa.classifiers.core.driftdetection.PageHinkleyDM
-
- PageHinkleyFading - Class in moa.classifiers.rules.driftdetection
-
- PageHinkleyFading(double, double) - Constructor for class moa.classifiers.rules.driftdetection.PageHinkleyFading
-
- PageHinkleyTest - Class in moa.classifiers.rules.driftdetection
-
- PageHinkleyTest(double, double) - Constructor for class moa.classifiers.rules.driftdetection.PageHinkleyTest
-
- paint(Graphics) - Method in class moa.gui.LineGraphViewPanel.PlotPanel
-
- paintAmplifiedPlot() - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
This method is used to paint line graph or scatter diagram in popup window from VisualizeFeature Tab.
- paintChildren(Graphics) - Method in class moa.gui.visualization.AbstractGraphCanvas
-
- paintComponent(Graphics) - Method in class moa.gui.clustertab.ClusteringVisualEvalPanel
-
- paintComponent(Graphics) - Method in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Paints this component
- paintComponent(Graphics) - Method in class moa.gui.featureanalysis.FeatureImportanceGraph
-
- paintComponent(Graphics) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
This override method is used to paint embedded line graph or scatter diagram in VisualizeFeature Tab.
- paintComponent(Graphics) - Method in class moa.gui.outliertab.OutlierVisualEvalPanel
-
- paintComponent(Graphics) - Method in class moa.gui.visualization.AbstractGraphAxes
-
- paintComponent(Graphics) - Method in class moa.gui.visualization.ClusterPanel
-
- paintComponent(Graphics) - Method in class moa.gui.visualization.GraphAxes
-
- paintComponent(Graphics) - Method in class moa.gui.visualization.GraphCanvas
-
- paintComponent(Graphics) - Method in class moa.gui.visualization.GraphCurve
-
- paintComponent(Graphics) - Method in class moa.gui.visualization.GraphMultiCurve
-
- paintComponent(Graphics) - Method in class moa.gui.visualization.GraphScatter
-
- paintComponent(Graphics) - Method in class moa.gui.visualization.OutlierPanel
-
- paintComponent(Graphics) - Method in class moa.gui.visualization.PointPanel
-
- paintStandardDeviation(Graphics, int, int, int) - Method in class moa.gui.visualization.AbstractGraphPlot
-
- paintValue(Graphics, Rectangle) - Method in class weka.gui.MOAClassOptionEditor
-
Paints a representation of the current Object.
- Pair<T> - Class in moa.clusterers.outliers.utils.mtree.utils
-
A pair of objects of the same type.
- Pair<T extends java.lang.Comparable<T>,U extends java.lang.Comparable<U>> - Class in moa.recommender.rc.utils
-
- Pair() - Constructor for class moa.clusterers.outliers.utils.mtree.utils.Pair
-
Creates a pair of null objects.
- Pair(double, int) - Constructor for class moa.classifiers.meta.DACC.Pair
-
- Pair(T, T) - Constructor for class moa.clusterers.outliers.utils.mtree.utils.Pair
-
Creates a pair with the objects specified in the arguments.
- Pair(T, U) - Constructor for class moa.recommender.rc.utils.Pair
-
- PairedLearners - Class in moa.classifiers.meta
-
Creates two classifiers: a stable and a reactive.
- PairedLearners() - Constructor for class moa.classifiers.meta.PairedLearners
-
- panel_size - Variable in class moa.gui.visualization.ClusterPanel
-
- panel_size - Variable in class moa.gui.visualization.OutlierPanel
-
- panel_size - Variable in class moa.gui.visualization.PointPanel
-
- parameterOption - Variable in class moa.clusterers.WekaClusteringAlgorithm
-
- parameters - Variable in class moa.clusterers.meta.Algorithm
-
- ParamGraphAxes - Class in moa.gui.visualization
-
ParamGraphAxes is an implementation of AbstractGraphAxes, drawing x labels
based on a parameter.
- ParamGraphAxes() - Constructor for class moa.gui.visualization.ParamGraphAxes
-
- ParamGraphCanvas - Class in moa.gui.visualization
-
ParamGraphCanvas is an implementation of AbstractGraphCanvas showing the
relation between a parameter and the measures.
- ParamGraphCanvas() - Constructor for class moa.gui.visualization.ParamGraphCanvas
-
Initialises a ProcessGraphCanvas by calling the super constructor with a
ParamGraphAxes as instance of AbstractGraphAxes and GraphScatter as
instance of AbstractGraphPlot.
- Pareja - Class in moa.gui.experimentertab.statisticaltests
-
T�tulo:
- Pareja() - Constructor for class moa.gui.experimentertab.statisticaltests.Pareja
-
- Pareja(double, double) - Constructor for class moa.gui.experimentertab.statisticaltests.Pareja
-
- parent - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- parent - Variable in class moa.classifiers.trees.ARFFIMTDD.Node
-
- parent - Variable in class moa.classifiers.trees.EFDT.FoundNode
-
- parent - Variable in class moa.classifiers.trees.FIMTDD.Node
-
- parent - Variable in class moa.classifiers.trees.HoeffdingOptionTree.FoundNode
-
- parent - Variable in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- parent - Variable in class moa.classifiers.trees.HoeffdingTree.FoundNode
-
- parent - Variable in class moa.classifiers.trees.iadem.Iadem2.Node
-
- parentBranch - Variable in class moa.classifiers.trees.EFDT.FoundNode
-
- parentBranch - Variable in class moa.classifiers.trees.HoeffdingOptionTree.FoundNode
-
- parentBranch - Variable in class moa.classifiers.trees.HoeffdingTree.FoundNode
-
- partition(double[], double[], int, int) - Static method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Partitions the instances around a pivot.
- partition(int, int[], int, int) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MedianOfWidestDimension
-
Partitions the instances around a pivot.
- partition(Instances, int[], int, int, int) - Static method in class moa.classifiers.lazy.neighboursearch.kdtrees.KMeansInpiredMethod
-
Partitions the instances around a pivot.
- PartitionFunction<DATA> - Interface in moa.clusterers.outliers.utils.mtree
-
An object with partitions a set of data into two sub-sets.
- PartitionFunctions - Class in moa.clusterers.outliers.utils.mtree
-
- PartitionFunctions.BalancedPartition<DATA> - Class in moa.clusterers.outliers.utils.mtree
-
A
partition function that tries to
distribute the data objects equally between the promoted data objects,
associating to each promoted data objects the nearest data objects.
- partitionIndex - Variable in class moa.streams.PartitioningStream
-
- partitionIndexOption - Variable in class moa.streams.PartitioningStream
-
- PartitioningStream - Class in moa.streams
-
This stream partitions the base stream into n distinct streams and outputs one of them
- PartitioningStream() - Constructor for class moa.streams.PartitioningStream
-
- partitionOptions(String[]) - Static method in class moa.core.Utils
-
Returns the secondary set of options (if any) contained in
the supplied options array.
- partitions - Variable in class moa.clusterers.outliers.utils.mtree.SplitFunction.SplitResult
-
A pair of partitions corresponding to the promoted data
objects.
- path - Variable in class moa.gui.experimentertab.Algorithm
-
- path - Variable in class moa.gui.experimentertab.Summary
-
The path of the results
- pause() - Static method in class moa.gui.visualization.RunOutlierVisualizer
-
- pause() - Static method in class moa.gui.visualization.RunVisualizer
-
- PAUSED - moa.gui.experimentertab.ExpTaskThread.Status
-
- PAUSED - moa.tasks.TaskThread.Status
-
- pauseFlag - Variable in class moa.tasks.StandardTaskMonitor
-
- pauseSelectedTasks() - Method in class moa.gui.active.ALTaskManagerPanel
-
- pauseSelectedTasks() - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- pauseSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- pauseSelectedTasks() - Method in class moa.gui.experimentertab.TaskManagerTabPanel
-
Pause tasks
- pauseSelectedTasks() - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- pauseSelectedTasks() - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- pauseSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
-
- pauseSelectedTasks() - Method in class moa.gui.TaskManagerPanel
-
- pauseTask() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- pauseTask() - Method in class moa.tasks.meta.ALTaskThread
-
- pauseTask() - Method in class moa.tasks.TaskThread
-
- pauseTaskButton - Variable in class moa.gui.active.ALTaskManagerPanel
-
- pauseTaskButton - Variable in class moa.gui.AuxiliarTaskManagerPanel
-
- pauseTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- pauseTaskButton - Variable in class moa.gui.MultiLabelTaskManagerPanel
-
- pauseTaskButton - Variable in class moa.gui.MultiTargetTaskManagerPanel
-
- pauseTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
-
- pauseTaskButton - Variable in class moa.gui.TaskManagerPanel
-
- paymentValues - Static variable in class moa.streams.generators.AssetNegotiationGenerator
-
- PDFCAIRO - moa.gui.experimentertab.PlotTab.Terminal
-
- PDFCAIRO - moa.tasks.Plot.Terminal
-
- peek() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap
-
peeks at the first element.
- penaltyFactorOption - Variable in class moa.classifiers.meta.LimAttClassifier
-
- percentageAnomalousAttributesOption - Variable in class moa.classifiers.rules.core.anomalydetection.AnomalinessRatioScore
-
- percentageThresholdOption - Variable in class moa.classifiers.rules.multilabel.inputselectors.MeritThreshold
-
- percentInCommon - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- perceptron - Variable in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- Perceptron - Class in moa.classifiers.functions
-
Single perceptron classifier.
- Perceptron - Class in moa.classifiers.rules.functions
-
- Perceptron() - Constructor for class moa.classifiers.functions.Perceptron
-
- Perceptron() - Constructor for class moa.classifiers.rules.functions.Perceptron
-
- Perceptron(Perceptron) - Constructor for class moa.classifiers.rules.functions.Perceptron
-
- perceptronattributeStatistics - Variable in class moa.classifiers.rules.functions.Perceptron
-
- perceptronInstancesSeen - Variable in class moa.classifiers.rules.functions.Perceptron
-
- perceptronsumY - Variable in class moa.classifiers.rules.functions.Perceptron
-
- perceptronYSeen - Variable in class moa.classifiers.rules.functions.Perceptron
-
- performanceMeasure - Variable in class moa.clusterers.meta.Algorithm
-
- period - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- periodOption - Variable in class moa.classifiers.meta.DynamicWeightedMajority
-
- periodOption - Variable in class moa.classifiers.meta.LearnNSE
-
- perturbValue(double, double, double) - Method in class moa.streams.generators.AgrawalGenerator
-
- perturbValue(double, double, double, double) - Method in class moa.streams.generators.AgrawalGenerator
-
- peturbFractionOption - Variable in class moa.streams.generators.AgrawalGenerator
-
- phinstancesSeen - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
-
- PHmin - Variable in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- PHmin - Variable in class moa.classifiers.trees.FIMTDD.InnerNode
-
- PHmins - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- PHmT - Variable in class moa.classifiers.rules.RuleClassification
-
- PHMT - Variable in class moa.classifiers.rules.RuleClassification
-
- PHsum - Variable in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- PHsum - Variable in class moa.classifiers.trees.FIMTDD.InnerNode
-
- PHsums - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- pID - Variable in class moa.evaluation.CMM_GTAnalysis.CMMPoint
-
point ID
- pineg - Variable in class moa.classifiers.meta.OCBoost
-
- pipos - Variable in class moa.classifiers.meta.OCBoost
-
- plot - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- plot - Variable in class moa.gui.featureanalysis.FeatureImportanceGraph
-
THe drawing tool provided by jmathplot.jar
- plot - Variable in class moa.gui.featureanalysis.FeatureImportancePanel
-
THe drawing tool provided by jmathplot.jar
- plot - Variable in class moa.gui.featureanalysis.LineAndScatterPanel
-
THe drawing tool provided by jmathplot.jar
- Plot - Class in moa.tasks
-
A task allowing to create and plot gnuplot scripts.
- Plot() - Constructor for class moa.tasks.Plot
-
- Plot.LegendLocation - Enum in moa.tasks
-
Location of the legend on the plot.
- Plot.LegendType - Enum in moa.tasks
-
Type of legend.
- Plot.PlotStyle - Enum in moa.tasks
-
- Plot.Terminal - Enum in moa.tasks
-
Plot output terminal.
- PlotLine() - Constructor for class moa.gui.LineGraphViewPanel.PlotLine
-
- plotLines - Variable in class moa.gui.LineGraphViewPanel
-
- plotOutputOption - Variable in class moa.tasks.Plot
-
FileOption for selecting the plot output file.
- plotPanel - Variable in class moa.gui.visualization.AbstractGraphCanvas
-
- PlotPanel() - Constructor for class moa.gui.LineGraphViewPanel.PlotPanel
-
- plotStyleOption - Variable in class moa.tasks.Plot
-
Type of plot - dots, points, lines ets.
- PlotTab - Class in moa.gui.experimentertab
-
Generate figures plotting the performance measurements of various learning
algorithms over time.
- PlotTab() - Constructor for class moa.gui.experimentertab.PlotTab
-
- PlotTab.LegendType - Enum in moa.gui.experimentertab
-
Lgend type
- PlotTab.PlotStyle - Enum in moa.gui.experimentertab
-
Plot style
- PlotTab.Terminal - Enum in moa.gui.experimentertab
-
Terminal
- PlotTableModel() - Constructor for class moa.gui.LineGraphViewPanel.PlotTableModel
-
- PminOption - Variable in class moa.classifiers.rules.RuleClassifier
-
- PNG - moa.gui.experimentertab.PlotTab.Terminal
-
- PNG - moa.tasks.Plot.Terminal
-
- Point - Class in moa.clusterers.streamkm
-
- Point(int) - Constructor for class moa.clusterers.streamkm.Point
-
- Point(Instance, int) - Constructor for class moa.clusterers.streamkm.Point
-
- pointIntervalOption - Variable in class moa.tasks.Plot
-
Interval between plotted data points.
- PointPanel - Class in moa.gui.visualization
-
- PointPanel(DataPoint, StreamPanel, double, double) - Constructor for class moa.gui.visualization.PointPanel
-
Type 1: Possibly be decayed, colored by class label.
- PointPanel(DataPoint, StreamPanel, Color) - Constructor for class moa.gui.visualization.PointPanel
-
Type 2: Never be decayed, single color.
- POINTS - moa.gui.experimentertab.PlotTab.PlotStyle
-
- POINTS - moa.tasks.Plot.PlotStyle
-
- poisson(double, Random) - Static method in class moa.core.MiscUtils
-
- polevl(double, double[], int) - Static method in class moa.core.Statistics
-
Evaluates the given polynomial of degree N at x.
- pOption - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM
-
- popupCopyRangeMenu(int, int) - Method in class moa.gui.featureanalysis.AttributeSelectionPanel
-
- popupCopyRangeMenu(int, int) - Method in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
- position - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- position - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator.Score
-
Age of example - position in the stream where the example was
added
- positionOffsetOption - Variable in class moa.clusterers.ClusterGenerator
-
- positionOption - Variable in class moa.streams.ConceptDriftRealStream
-
- positionOption - Variable in class moa.streams.ConceptDriftStream
-
- posSamples - Variable in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- postProcessDistances(double[]) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction
-
Does post processing of the distances (if necessary) returned by
distance(distance(Instance first, Instance second, double cutOffValue).
- postProcessDistances(double[]) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance
-
Does post processing of the distances (if necessary) returned by
distance(distance(Instance first, Instance second, double cutOffValue).
- postProcessDistances(double[]) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Does nothing, derived classes may override it though.
- POSTSCRIPT - moa.gui.experimentertab.PlotTab.Terminal
-
- POSTSCRIPT - moa.tasks.Plot.Terminal
-
- POSTSCRIPT_COLOR - moa.gui.experimentertab.PlotTab.Terminal
-
- POSTSCRIPT_COLOR - moa.tasks.Plot.Terminal
-
- posWindow - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator.Estimator
-
- posWindow - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator.Estimator
-
- posWindow - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- posWindow - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator.Score
-
Age of example - position in the window where the example was
added
- posWindow - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator.WindowEstimator
-
- posWindow - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
-
- powerSeries(double, double, double) - Static method in class moa.core.Statistics
-
Power series for incomplete beta integral.
- preciseThreadTimesAvailable - Static variable in class moa.core.TimingUtils
-
- precision - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- precisionPerClassOption - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- precisionRecallOutputOption - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- predicate - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.SplitNode
-
- predicate - Variable in class moa.classifiers.rules.multilabel.core.AttributeExpansionSuggestion
-
- predicate - Variable in class moa.classifiers.rules.multilabel.core.Literal
-
- Predicate - Interface in moa.classifiers.rules.core
-
- Predicates - Class in moa.classifiers.rules
-
- Predicates(double, double, double) - Constructor for class moa.classifiers.rules.Predicates
-
- predicateSet - Variable in class moa.classifiers.rules.RuleClassification
-
- prediction - Variable in class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- prediction - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- prediction - Variable in class moa.clusterers.meta.Algorithm
-
- prediction(double[]) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.MultitargetPerceptron
-
Output the prediction made by this perceptron on the given instance
- prediction(double[]) - Method in class moa.classifiers.rules.functions.Perceptron
-
- prediction(double[][], int) - Method in class moa.classifiers.meta.LimAttClassifier
-
- prediction(Instance) - Method in class moa.classifiers.trees.ARFFIMTDD.FIMTDDPerceptron
-
- prediction(Instance) - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
-
- prediction(Instance, int) - Method in class moa.classifiers.functions.Perceptron
-
- prediction(DoubleVector) - Method in class moa.classifiers.trees.ARFFIMTDD.FIMTDDPerceptron
-
Output the prediction made by this perceptron on the given instance
- prediction(DoubleVector) - Method in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
-
Output the prediction made by this perceptron on the given instance
- Prediction - Interface in com.yahoo.labs.samoa.instances
-
- predictionFunction - Variable in class moa.classifiers.rules.core.Rule.Builder
-
- predictionFunction - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- predictionFunction(int) - Method in class moa.classifiers.rules.core.Rule.Builder
-
- predictionFunctionOption - Variable in class moa.classifiers.rules.AMRulesRegressorOld
-
- predictionFunctionOption - Variable in class moa.classifiers.rules.RuleClassifier
-
- predictionOption - Variable in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
-
- predictionPruning(double[][], int[], int) - Method in class moa.classifiers.meta.LimAttClassifier
-
- predictions - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- predictPerformance(Algorithm) - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- predictRating(float[], float[]) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- predictRating(int, int) - Method in class moa.recommender.predictor.BaselinePredictor
-
- predictRating(int, int) - Method in class moa.recommender.predictor.BRISMFPredictor
-
- predictRating(int, int) - Method in interface moa.recommender.predictor.RatingPredictor
-
- predictRating(int, int) - Method in class moa.recommender.rc.predictor.impl.BaselinePredictor
-
- predictRating(int, int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- predictRating(int, int) - Method in interface moa.recommender.rc.predictor.RatingPredictor
-
- predictRating(Integer, Integer) - Method in class moa.recommender.predictor.BaselinePredictor
-
- predictRating(Integer, Integer) - Method in class moa.recommender.predictor.BRISMFPredictor
-
- predictRatings(int, List<Integer>) - Method in class moa.recommender.predictor.BaselinePredictor
-
- predictRatings(int, List<Integer>) - Method in class moa.recommender.predictor.BRISMFPredictor
-
- predictRatings(int, List<Integer>) - Method in interface moa.recommender.predictor.RatingPredictor
-
- predictRatings(int, List<Integer>) - Method in class moa.recommender.rc.predictor.impl.BaselinePredictor
-
- predictRatings(int, List<Integer>) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- predictRatings(int, List<Integer>) - Method in interface moa.recommender.rc.predictor.RatingPredictor
-
- preds - Variable in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
-
- prepareClassOptions() - Method in class com.github.javacliparser.JavaCLIParser
-
Prepares the options of this class.
- prepareClassOptions(TaskMonitor, ObjectRepository) - Method in class moa.options.AbstractOptionHandler
-
Prepares the options of this class.
- prepareClassOptions(TaskMonitor, ObjectRepository) - Method in class moa.options.OptionsHandler
-
Prepares the options of this class.
- prepareForUse() - Method in class moa.options.AbstractOptionHandler
-
- prepareForUse() - Method in interface moa.options.OptionHandler
-
This method prepares this object for use.
- prepareForUse() - Method in class moa.options.OptionsHandler
-
Dictionary with option texts and objects
- prepareForUse(TaskMonitor, ObjectRepository) - Method in class moa.options.AbstractOptionHandler
-
- prepareForUse(TaskMonitor, ObjectRepository) - Method in interface moa.options.OptionHandler
-
This method prepares this object for use.
- prepareForUse(TaskMonitor, ObjectRepository) - Method in class moa.options.OptionsHandler
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.AbstractClassifier
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.active.budget.FixedBM
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.ADWINChangeDetector
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.CusumDM
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.DDM
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.EDDM
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.EWMAChartDM
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.PageHinkleyDM
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.RDDM
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.driftdetection.STEPD
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.splitcriteria.GiniSplitCriterion
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.splitcriteria.InfoGainSplitCriterion
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.splitcriteria.VarianceReductionSplitCriterion
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.statisticaltests.Cramer
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.core.statisticaltests.KNN
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.multilabel.core.splitcriteria.ICVarianceReduction
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.core.anomalydetection.AnomalinessRatioScore
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.core.anomalydetection.NoAnomalyDetection
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.core.anomalydetection.OddsRatioScore
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.CantellisInequality
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.ChebyshevInequality
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.core.anomalydetection.probabilityfunctions.GaussInequality
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.core.changedetection.NoChangeDetection
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.core.splitcriteria.VarianceRatioSplitCriterion
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.featureranking.AbstractFeatureRanking
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelNominalAttributeObserver
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteralClassification
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteralRegression
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultilabelInformationGain
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.core.splitcriteria.MultiTargetVarianceRatio
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.errormeasurers.AbstractMultiLabelErrorMeasurer
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.inputselectors.MeritThreshold
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.inputselectors.SelectAllInputs
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.outputselectors.EntropyThreshold
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.outputselectors.SelectAllOutputs
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.outputselectors.StdDevThreshold
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.rules.multilabel.outputselectors.VarianceThreshold
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.clusterers.AbstractClusterer
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.options.AbstractOptionHandler
-
This method describes the implementation of how to prepare this object for use.
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.data.MemRecommenderData
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.dataset.impl.FlixsterDataset
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.dataset.impl.JesterDataset
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.dataset.impl.MovielensDataset
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.predictor.BaselinePredictor
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.recommender.predictor.BRISMFPredictor
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.ArffFileStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.BootstrappedStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.clustering.FileStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.clustering.SimpleCSVStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.ConceptDriftRealStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.ConceptDriftStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.FilteredStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.filters.AbstractMultiLabelStreamFilter
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.filters.AbstractStreamFilter
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.AgrawalGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.AssetNegotiationGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.HyperplaneGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.LEDGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.LEDGeneratorDrift
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.MixedGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.RandomRBFGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.RandomTreeGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.SEAGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.SineGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.STAGGERGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.TextGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.WaveformGenerator
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.generators.WaveformGeneratorDrift
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.ImbalancedStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.IrrelevantFeatureAppenderStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.MultiFilteredStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.MultiLabelFilteredStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.MultiTargetArffFileStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.PartitioningStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.streams.RecurrentConceptDriftStream
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.tasks.AbstractTask
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.tasks.meta.ALMultiParamTask
-
- prepareForUseImpl(TaskMonitor, ObjectRepository) - Method in class moa.tasks.meta.ALPartitionEvaluationTask
-
- prepareRandomSubspaceInstance(Instance, double) - Method in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- PreprocessDefaults() - Constructor for class moa.gui.featureanalysis.VisualizeFeaturesPanel.PreprocessDefaults
-
- prequentialEvaluationTaskOption - Variable in class moa.tasks.meta.ALMultiParamTask
-
- preventRemoval - Variable in class moa.clusterers.meta.Algorithm
-
- Preview - Class in moa.evaluation.preview
-
Abstract class which is used to define the methods needed from a preview
- Preview() - Constructor for class moa.evaluation.preview.Preview
-
- PreviewCollection<CollectionElementType extends Preview> - Class in moa.evaluation.preview
-
Class that stores and keeps the history of multiple previews
- PreviewCollection(String, String, Class<?>) - Constructor for class moa.evaluation.preview.PreviewCollection
-
- PreviewCollection(String, String, Class<?>, String, double[]) - Constructor for class moa.evaluation.preview.PreviewCollection
-
- PreviewCollectionLearningCurveWrapper - Class in moa.evaluation.preview
-
Class used to wrap LearningCurve so that it can be used in
conjunction with a PreviewCollection
- PreviewCollectionLearningCurveWrapper(LearningCurve, Class<?>) - Constructor for class moa.evaluation.preview.PreviewCollectionLearningCurveWrapper
-
- previewedThread - Variable in class moa.gui.active.ALPreviewPanel
-
- previewedThread - Variable in class moa.gui.experimentertab.ExpPreviewPanel
-
- previewedThread - Variable in class moa.gui.PreviewPanel
-
- PreviewExperiments - Class in moa.gui.experimentertab
-
- PreviewExperiments(ExpPreviewPanel) - Constructor for class moa.gui.experimentertab.PreviewExperiments
-
- previewLabel - Variable in class moa.gui.active.ALPreviewPanel
-
- previewLabel - Variable in class moa.gui.experimentertab.ExpPreviewPanel
-
- previewLabel - Variable in class moa.gui.PreviewPanel
-
- previewPanel - Variable in class moa.gui.active.ALTaskManagerPanel
-
- previewPanel - Variable in class moa.gui.ALTabPanel
-
- previewPanel - Variable in class moa.gui.AuxiliarTabPanel
-
- previewPanel - Variable in class moa.gui.AuxiliarTaskManagerPanel
-
- previewPanel - Variable in class moa.gui.ClassificationTabPanel
-
- previewPanel - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- previewPanel - Variable in class moa.gui.ConceptDriftTabPanel
-
- previewPanel - Variable in class moa.gui.experimentertab.ExperimenterTabPanel
-
- previewPanel - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- previewPanel - Variable in class moa.gui.MultiLabelTabPanel
-
- previewPanel - Variable in class moa.gui.MultiLabelTaskManagerPanel
-
- previewPanel - Variable in class moa.gui.MultiTargetTabPanel
-
- previewPanel - Variable in class moa.gui.MultiTargetTaskManagerPanel
-
- previewPanel - Variable in class moa.gui.RegressionTabPanel
-
- previewPanel - Variable in class moa.gui.RegressionTaskManagerPanel
-
- previewPanel - Variable in class moa.gui.TaskLauncher
-
- previewPanel - Variable in class moa.gui.TaskManagerPanel
-
- PreviewPanel - Class in moa.gui
-
This panel displays the running task preview text and buttons.
- PreviewPanel() - Constructor for class moa.gui.PreviewPanel
-
- PreviewPanel(PreviewPanel.TypePanel) - Constructor for class moa.gui.PreviewPanel
-
- PreviewPanel(PreviewPanel.TypePanel, CDTaskManagerPanel) - Constructor for class moa.gui.PreviewPanel
-
- PreviewPanel.TypePanel - Enum in moa.gui
-
- PreviewTableModel - Class in moa.gui
-
Class to display the latest preview in a table
- PreviewTableModel() - Constructor for class moa.gui.PreviewTableModel
-
- previousState - Variable in class moa.classifiers.meta.RCD
-
- previousWeight - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- previousWeight - Variable in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- previousWeight - Variable in class moa.classifiers.trees.FIMTDD.InnerNode
-
- priceValues - Static variable in class moa.streams.generators.AssetNegotiationGenerator
-
- print(String) - Method in interface moa.clusterers.outliers.MyBaseOutlierDetector.PrintMsg
-
- print(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
-
- Print(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- Print_lt_cnt(ArrayList<Integer>) - Method in class moa.clusterers.outliers.AbstractC.AbstractCBase
-
- printAnomaliesSupervised(StringBuilder, int) - Method in class moa.classifiers.rules.RuleClassifier
-
- printAnomaliesUnsupervised(StringBuilder, int) - Method in class moa.classifiers.rules.RuleClassifier
-
- printAnomaly(Instance, double) - Method in class moa.classifiers.rules.core.anomalydetection.OddsRatioScore
-
- printClusterCenter(Writer) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Writes the cluster center to a given stream.
- printClusteringCenters(Writer) - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Writes all clustering centers of the ClusterFeatures of the tree with this
node as the root to a given stream.
- printDStreamState() - Method in class moa.clusterers.dstream.Dstream
-
Prints out the values of the parameters associated with this instance of the D-Stream algorithm:
gap;
decay factor (lambda);
C_m and C_l;
D_m and D_l; and
beta.
- PrintEventQueue() - Method in class moa.clusterers.outliers.MCOD.MCODBase
-
- PrintEventQueue() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- printf(String, Object...) - Method in interface moa.clusterers.outliers.MyBaseOutlierDetector.PrintMsg
-
- printf(String, Object...) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
-
- Printf(String, Object...) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- printGridClusters() - Method in class moa.clusterers.dstream.Dstream
-
Iterates through cluster_list and prints out each grid cluster therein as a string.
- printGridList() - Method in class moa.clusterers.dstream.Dstream
-
Iterates through grid_list and prints out each density grid therein as a string.
- printInst(Instance) - Method in class moa.clusterers.dstream.Dstream
-
- PrintInstance(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- PrintISB() - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- printList() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
Prints out the contents of the neighborlist.
- println(String) - Method in interface moa.clusterers.outliers.MyBaseOutlierDetector.PrintMsg
-
- println(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
-
- Println(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- PrintMCSet(Set<MicroCluster>) - Method in class moa.clusterers.outliers.MCOD.MCODBase
-
- printMicroClusteringResult(Writer) - Method in class moa.clusterers.kmeanspm.BICO
-
Writes all micro cluster to a given stream.
- printNode() - Method in class moa.classifiers.oneclass.HSTreeNode
-
Prints this node to string and, if it is an internal node, prints its children nodes as well.
- PrintNodeList(List<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.MCOD.MCODBase
-
- PrintNodeList(List<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- PrintNodeSet(Set<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.MCOD.MCODBase
-
- PrintNodeSet(Set<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- PrintNodeVector(Vector<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.MCOD.MCODBase
-
- PrintNodeVector(Vector<ISBIndex.ISBNode>) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- PrintOutliers() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- PrintPD() - Method in class moa.clusterers.outliers.MCOD.MCODBase
-
- PrintPrecNeighs() - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM.ISBNodeExact
-
- printRule() - Method in class moa.classifiers.rules.core.Rule
-
- PrintRuleSet() - Method in class moa.classifiers.rules.AbstractAMRules
-
- PrintRuleSet() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- PrintRuleSet() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- printWeightsOption - Variable in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- priors - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- priors_norm - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- prob - Variable in class moa.classifiers.lazy.kNNwithPAW
-
- prob - Variable in class moa.classifiers.lazy.kNNwithPAWandADWIN
-
- probabilityDensity(double) - Method in class moa.core.GaussianEstimator
-
- ProbabilityFunction - Interface in moa.classifiers.rules.core.anomalydetection.probabilityfunctions
-
- probabilityFunctionOption - Variable in class moa.classifiers.rules.core.anomalydetection.AnomalinessRatioScore
-
- probabilityFunctionOption - Variable in class moa.classifiers.rules.core.anomalydetection.OddsRatioScore
-
- probabilityOfAttributeValueGivenClass(double, int) - Method in interface moa.classifiers.core.attributeclassobservers.AttributeClassObserver
-
Gets the probability for an attribute value given a class
- probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
-
- probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
-
- probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
-
- probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.GaussianNumericAttributeClassObserver
-
- probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.GreenwaldKhannaNumericAttributeClassObserver
-
- probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.NominalAttributeClassObserver
-
- probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.NullAttributeClassObserver
-
- probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.core.attributeclassobservers.VFMLNumericAttributeClassObserver
-
- probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- probabilityOfAttributeValueGivenClass(double, int) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- probabilityThresholdOption - Variable in class moa.classifiers.rules.RuleClassifier
-
- probNegative - Variable in class moa.streams.generators.TextGenerator
-
- probPerClass - Variable in class moa.streams.ImbalancedStream
-
- probPositive - Variable in class moa.streams.generators.TextGenerator
-
- probRound(double, Random) - Static method in class moa.core.Utils
-
Rounds a double to the next nearest integer value in a probabilistic
fashion (e.g.
- probToLogOdds(double) - Static method in class moa.core.Utils
-
Returns the log-odds for a given probabilitiy.
- proccesCMD() - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- process(Set<DATA>, DistanceFunction<? super DATA>) - Method in class moa.clusterers.outliers.utils.mtree.ComposedSplitFunction
-
- process(Set<DATA>, DistanceFunction<? super DATA>) - Method in interface moa.clusterers.outliers.utils.mtree.PromotionFunction
-
Chooses (promotes) a pair of objects according to some criteria that is
suitable for the application using the M-Tree.
- process(Set<DATA>, DistanceFunction<? super DATA>) - Method in class moa.clusterers.outliers.utils.mtree.PromotionFunctions.RandomPromotion
-
- process(Set<DATA>, DistanceFunction<? super DATA>) - Method in interface moa.clusterers.outliers.utils.mtree.SplitFunction
-
Processes the splitting of a node.
- process(Pair<DATA>, Set<DATA>, DistanceFunction<? super DATA>) - Method in interface moa.clusterers.outliers.utils.mtree.PartitionFunction
-
Executes the partitioning.
- process(Pair<DATA>, Set<DATA>, DistanceFunction<? super DATA>) - Method in class moa.clusterers.outliers.utils.mtree.PartitionFunctions.BalancedPartition
-
Processes the balanced partition.
- processChunk() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Processes a chunk of instances.
- processChunk() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Processes a chunk.
- processedInstances - Variable in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
Number of processed examples.
- processedInstances - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- processedInstances - Variable in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
Number of processed examples.
- processFiles() - Method in class moa.gui.experimentertab.ReadFile
-
Processes the results files of the algorithms in each directory.
- ProcessGraphAxes - Class in moa.gui.visualization
-
ProcessGraphAxes is an implementation of AbstractGraphAxes, drawing x labels
based on the process frequency.
- ProcessGraphAxes() - Constructor for class moa.gui.visualization.ProcessGraphAxes
-
- ProcessGraphCanvas - Class in moa.gui.visualization
-
ProcessGraphCanvas is an implementation of AbstractGraphCanvas, showing one
or multiple curves over a process.
- ProcessGraphCanvas() - Constructor for class moa.gui.visualization.ProcessGraphCanvas
-
Initialises a ProcessGraphCanvas by calling the super constructor with a
ProcessGraphAxes as instance of AbstractGraphAxes and GraphMultiCurve as
instance of AbstractGraphPlot.
- processingSpeed - Variable in class moa.clusterers.denstream.WithDBSCAN
-
- processInstance(Instance, ARFFIMTDD.Node, double, double, boolean, boolean) - Method in class moa.classifiers.trees.ARFFIMTDD
-
- processInstance(Instance, FIMTDD.Node, double, double, boolean, boolean) - Method in class moa.classifiers.trees.FIMTDD
-
- processInstance(Instance, FIMTDD.Node, double, double, boolean, boolean) - Method in class moa.classifiers.trees.ORTO
-
- processInstance(MultiLabelInstance, ISOUPTree.Node, double[], double[], boolean, boolean) - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- processInstanceOptionNode(Instance, ORTO.OptionNode, double, double, boolean, boolean) - Method in class moa.classifiers.trees.ORTO
-
- processNewInstanceImpl(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.AbstractC.AbstractC
-
- ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.Angiulli.ApproxSTORM
-
- ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.Angiulli.ExactSTORM
-
- ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.AnyOut.AnyOut
-
- ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.MCOD.MCOD
-
- ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- ProcessNewStreamObj(Instance) - Method in class moa.clusterers.outliers.SimpleCOD.SimpleCOD
-
- progressAnimSequence - Static variable in class moa.DoTask
-
Array of characters to use to animate the progress of tasks running.
- progressAnimSequence - Static variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
Array of characters to use to animate the progress of tasks running.
- progressBar - Variable in class moa.gui.featureanalysis.FeatureImportancePanel
-
Use progress bar to show the progress of computing scores of feature importance.
- progressBar - Variable in class moa.tasks.FeatureImportanceConfig
-
Use progress bar to show the progress of computing scores of feature importance.
- ProgressCellRenderer() - Constructor for class moa.gui.active.ALTaskManagerPanel.ProgressCellRenderer
-
- ProgressCellRenderer() - Constructor for class moa.gui.AuxiliarTaskManagerPanel.ProgressCellRenderer
-
- ProgressCellRenderer() - Constructor for class moa.gui.conceptdrift.CDTaskManagerPanel.ProgressCellRenderer
-
- ProgressCellRenderer() - Constructor for class moa.gui.experimentertab.TaskManagerTabPanel.ProgressCellRenderer
-
ProgressCellRenderer Constructor
- ProgressCellRenderer() - Constructor for class moa.gui.MultiLabelTaskManagerPanel.ProgressCellRenderer
-
- ProgressCellRenderer() - Constructor for class moa.gui.MultiTargetTaskManagerPanel.ProgressCellRenderer
-
- ProgressCellRenderer() - Constructor for class moa.gui.RegressionTaskManagerPanel.ProgressCellRenderer
-
- ProgressCellRenderer() - Constructor for class moa.gui.TaskManagerPanel.ProgressCellRenderer
-
- progressLabel - Variable in class moa.gui.featureanalysis.FeatureImportancePanel
-
- promoteCandidatesIntoEnsemble() - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- promoted - Variable in class moa.clusterers.outliers.utils.mtree.SplitFunction.SplitResult
-
A pair of promoted data objects.
- PromotionFunction<DATA> - Interface in moa.clusterers.outliers.utils.mtree
-
An object that chooses a pair from a set of data objects.
- PromotionFunctions - Class in moa.clusterers.outliers.utils.mtree
-
- PromotionFunctions.RandomPromotion<DATA> - Class in moa.clusterers.outliers.utils.mtree
-
- PROPERTIES - Static variable in class moa.gui.GUIDefaults
-
Properties associated with the GUI options.
- PropertiesReader - Class in moa.core
-
Class implementing some properties reader utility methods.
- PropertiesReader() - Constructor for class moa.core.PropertiesReader
-
- PROPERTY_FILE - Static variable in class moa.gui.GUIDefaults
-
The name of the properties file.
- prunedAlternateTrees - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree
-
- pruneOption - Variable in class moa.classifiers.meta.LimAttClassifier
-
- pruneOption - Variable in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- pruneToK(int) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.NeighborList
-
Prunes the list to contain the k nearest neighbors.
- pruning - Variable in class moa.classifiers.meta.LearnNSE
-
- pruningStrategyOption - Variable in class moa.classifiers.meta.LearnNSE
-
- PSLATEX - moa.gui.experimentertab.PlotTab.Terminal
-
- PSLATEX - moa.tasks.Plot.Terminal
-
- PSTEX - moa.gui.experimentertab.PlotTab.Terminal
-
- PSTEX - moa.tasks.Plot.Terminal
-
- PSTRICKS - moa.gui.experimentertab.PlotTab.Terminal
-
- PSTRICKS - moa.tasks.Plot.Terminal
-
- pureBoostOption - Variable in class moa.classifiers.meta.ADOB
-
- pureBoostOption - Variable in class moa.classifiers.meta.BOLE
-
- pureBoostOption - Variable in class moa.classifiers.meta.OzaBoost
-
- pureBoostOption - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- purpose - Variable in class com.github.javacliparser.AbstractOption
-
Text of the purpose of this option.
- put(int, double) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap
-
adds the value to the heap.
- put(long, T) - Method in class moa.clusterers.kmeanspm.CuckooHashing
-
Adds an element to the hash table.
- putBySubstitute(int, double) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap
-
Puts an element by substituting it in place of
the top most element.
- putKthNearest(int, double) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap
-
Stores kth nearest elements (if there are
more than one).
- PValue - Variable in class moa.gui.experimentertab.statisticaltests.PValuePerTwoAlgorithm
-
- PValuePerTwoAlgorithm - Class in moa.gui.experimentertab.statisticaltests
-
- PValuePerTwoAlgorithm(String, String, double) - Constructor for class moa.gui.experimentertab.statisticaltests.PValuePerTwoAlgorithm
-
Costructor.
- r - Variable in class moa.streams.filters.RBFFilter
-
- R_MAX - Static variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Index in ranges for MAX.
- R_MIN - Static variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Index in ranges for MIN.
- R_WIDTH - Static variable in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Index in ranges for WIDTH.
- radius() - Method in class moa.cluster.Miniball
-
Return the Radius of the miniball
- radiusDecreaseOption - Variable in class moa.clusterers.ClusterGenerator
-
- radiusFactor - Variable in class moa.cluster.CFCluster
-
- radiusIncreaseOption - Variable in class moa.clusterers.ClusterGenerator
-
- radiusOption - Variable in class moa.clusterers.outliers.AbstractC.AbstractC
-
- radiusOption - Variable in class moa.clusterers.outliers.Angiulli.ApproxSTORM
-
- radiusOption - Variable in class moa.clusterers.outliers.Angiulli.ExactSTORM
-
- radiusOption - Variable in class moa.clusterers.outliers.MCOD.MCOD
-
- radiusOption - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCOD
-
- random - Variable in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- random - Variable in class moa.streams.ConceptDriftRealStream
-
- random - Variable in class moa.streams.ConceptDriftStream
-
- random - Variable in class moa.streams.filters.AddNoiseFilter
-
- random - Variable in class moa.streams.filters.RBFFilter
-
- random - Variable in class moa.streams.filters.ReLUFilter
-
- random - Variable in class moa.streams.ImbalancedStream
-
- random - Variable in class moa.streams.IrrelevantFeatureAppenderStream
-
A pseudo-random number generator.
- random - Variable in class moa.streams.PartitioningStream
-
- RandomAMRules - Class in moa.classifiers.rules.meta
-
Random AMRules algoritgm that performs analogous procedure as the Random Forest Trees but with Rules
- RandomAMRules() - Constructor for class moa.classifiers.rules.meta.RandomAMRules
-
- RandomAMRulesOld - Class in moa.classifiers.rules.meta
-
- RandomAMRulesOld() - Constructor for class moa.classifiers.rules.meta.RandomAMRulesOld
-
- randomFlagOne - Variable in class moa.tasks.WriteMultipleStreamsToARFF
-
- randomFlagTwo - Variable in class moa.tasks.WriteMultipleStreamsToARFF
-
- randomGenerator - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- randomGenerator - Variable in class moa.streams.BootstrappedStream
-
- RandomHoeffdingTree - Class in moa.classifiers.trees
-
Random decision trees for data streams.
- RandomHoeffdingTree() - Constructor for class moa.classifiers.trees.RandomHoeffdingTree
-
- RandomHoeffdingTree.LearningNodeNB - Class in moa.classifiers.trees
-
- RandomHoeffdingTree.LearningNodeNBAdaptive - Class in moa.classifiers.trees
-
- RandomHoeffdingTree.RandomLearningNode - Class in moa.classifiers.trees
-
- randomize(Random) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Randomize.
- RandomLearningNode(double[]) - Constructor for class moa.classifiers.trees.RandomHoeffdingTree.RandomLearningNode
-
- RandomLearningNode(double[], int) - Constructor for class moa.classifiers.trees.ARFHoeffdingTree.RandomLearningNode
-
- randomOneOption - Variable in class moa.tasks.WriteMultipleStreamsToARFF
-
- RandomPromotion() - Constructor for class moa.clusterers.outliers.utils.mtree.PromotionFunctions.RandomPromotion
-
- RandomRBFGenerator - Class in moa.streams.generators
-
Stream generator for a random radial basis function stream.
- RandomRBFGenerator() - Constructor for class moa.streams.generators.RandomRBFGenerator
-
- RandomRBFGenerator.Centroid - Class in moa.streams.generators
-
- RandomRBFGeneratorDrift - Class in moa.streams.generators
-
Stream generator for a random radial basis function stream with drift.
- RandomRBFGeneratorDrift() - Constructor for class moa.streams.generators.RandomRBFGeneratorDrift
-
- RandomRBFGeneratorEvents - Class in moa.streams.clustering
-
- RandomRBFGeneratorEvents() - Constructor for class moa.streams.clustering.RandomRBFGeneratorEvents
-
- RandomRules - Class in moa.classifiers.meta
-
- RandomRules() - Constructor for class moa.classifiers.meta.RandomRules
-
- randomSample(Collection<T>, int) - Static method in class moa.clusterers.outliers.utils.mtree.utils.Utils
-
Randomly chooses elements from the collection.
- randomSeed - Variable in class moa.classifiers.AbstractClassifier
-
Random seed used in randomizable learners
- randomSeed - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaLearningNode
-
- randomSeed - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree.AdaSplitNode
-
- randomSeed - Variable in class moa.clusterers.AbstractClusterer
-
- randomSeedOption - Variable in class moa.classifiers.AbstractClassifier
-
Option for randomizable learners to change the random seed
- randomSeedOption - Variable in class moa.classifiers.multitarget.BasicMultiLabelLearner
-
- randomSeedOption - Variable in class moa.classifiers.multitarget.BasicMultiTargetRegressor
-
- randomSeedOption - Variable in class moa.classifiers.rules.functions.Perceptron
-
- randomSeedOption - Variable in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- randomSeedOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- randomSeedOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- randomSeedOption - Variable in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- randomSeedOption - Variable in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- randomSeedOption - Variable in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- randomSeedOption - Variable in class moa.clusterers.AbstractClusterer
-
- randomSeedOption - Variable in class moa.clusterers.CobWeb
-
- randomSeedOption - Variable in class moa.clusterers.streamkm.StreamKM
-
- randomSeedOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedTestThenTrain
-
- randomSeedOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequentialCV
-
- randomSeedOption - Variable in class moa.streams.BootstrappedStream
-
- randomSeedOption - Variable in class moa.streams.ConceptDriftRealStream
-
- randomSeedOption - Variable in class moa.streams.ConceptDriftStream
-
- randomSeedOption - Variable in class moa.streams.filters.AddNoiseFilter
-
- randomSeedOption - Variable in class moa.streams.filters.RBFFilter
-
- randomSeedOption - Variable in class moa.streams.filters.ReLUFilter
-
- randomSeedOption - Variable in class moa.streams.PartitioningStream
-
- randomSeedOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- randomSeedOption - Variable in class moa.tasks.EvaluatePrequentialCV
-
- randomSeedOption - Variable in class moa.tasks.EvaluatePrequentialDelayedCV
-
- randomSeedOption - Variable in class moa.tasks.meta.ALPartitionEvaluationTask
-
- RandomTreeGenerator - Class in moa.streams.generators
-
Stream generator for a stream based on a randomly generated tree..
- RandomTreeGenerator() - Constructor for class moa.streams.generators.RandomTreeGenerator
-
- RandomTreeGenerator.Node - Class in moa.streams.generators
-
- randomTwoOption - Variable in class moa.tasks.WriteMultipleStreamsToARFF
-
- range - Variable in class com.yahoo.labs.samoa.instances.ArffLoader
-
- range - Variable in class com.yahoo.labs.samoa.instances.InstanceInformation
-
Range for multi-label instances.
- Range - Class in com.yahoo.labs.samoa.instances
-
- Range(String) - Constructor for class com.yahoo.labs.samoa.instances.Range
-
- RangeOption - Class in com.github.javacliparser
-
Range option.
- RangeOption(String, char, String, String) - Constructor for class com.github.javacliparser.RangeOption
-
- RangeOptionEditComponent - Class in com.github.javacliparser.gui
-
An OptionEditComponent that lets the user edit a range option.
- RangeOptionEditComponent(Option) - Constructor for class com.github.javacliparser.gui.RangeOptionEditComponent
-
- RangeSearch(ISBIndex.ISBNode, double) - Method in class moa.clusterers.outliers.AbstractC.ISBIndex
-
- RangeSearch(ISBIndex.ISBNode, double) - Method in class moa.clusterers.outliers.Angiulli.ISBIndex
-
- RangeSearch(ISBIndex.ISBNode, double) - Method in class moa.clusterers.outliers.MCOD.ISBIndex
-
- RangeSearch(ISBIndex.ISBNode, double) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex
-
- rangeSingle(String) - Method in class com.yahoo.labs.samoa.instances.Range
-
Translates a single string selection into it's internal 0-based
equivalent.
- rangesSet() - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Check if ranges are set.
- rank - Variable in class moa.gui.experimentertab.statisticaltests.RankPerAlgorithm
-
- RankingGraph - Class in moa.gui.experimentertab
-
Shows the comparison of several online learning algorithms on multiple
datasets by performing appropriate statistical tests.
- RankingGraph(ArrayList<RankPerAlgorithm>, ArrayList<PValuePerTwoAlgorithm>, String, double) - Constructor for class moa.gui.experimentertab.RankingGraph
-
Class constructor.
- RankingGraph.SliderPanel - Class in moa.gui.experimentertab
-
Allows you to increase or decrease the scale of the graph.
- RankPerAlgorithm - Class in moa.gui.experimentertab.statisticaltests
-
This class contains each algorithm with its ranking.
- RankPerAlgorithm(String, double) - Constructor for class moa.gui.experimentertab.statisticaltests.RankPerAlgorithm
-
Constructor.
- rating - Variable in class moa.recommender.rc.utils.Rating
-
- Rating - Class in moa.recommender.rc.utils
-
- Rating(int, int, double) - Constructor for class moa.recommender.rc.utils.Rating
-
- ratingIterator() - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- ratingIterator() - Method in interface moa.recommender.rc.data.RecommenderData
-
- RatingPredictor - Interface in moa.recommender.predictor
-
Rating predicting algorithm.
- RatingPredictor - Interface in moa.recommender.rc.predictor
-
- ratingPredictorOption - Variable in class moa.tasks.EvaluateOnlineRecommender
-
- ratingsItem - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
-
- ratingsUser - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
-
- RawCellBuilder - Class in moa.tasks.ipynb
-
Implement a raw cell
- RawCellBuilder() - Constructor for class moa.tasks.ipynb.RawCellBuilder
-
- RBFFilter - Class in moa.streams.filters
-
- RBFFilter() - Constructor for class moa.streams.filters.RBFFilter
-
- RCD - Class in moa.classifiers.meta
-
Creates a set of classifiers, each one representing a different context.
- RCD() - Constructor for class moa.classifiers.meta.RCD
-
- RDDM - Class in moa.classifiers.core.driftdetection
-
- RDDM() - Constructor for class moa.classifiers.core.driftdetection.RDDM
-
- reactiveLearner - Variable in class moa.classifiers.meta.PairedLearners
-
- reactiveLearnerOption - Variable in class moa.classifiers.meta.PairedLearners
-
- read() - Method in class moa.core.InputStreamProgressMonitor
-
- read(byte[]) - Method in class moa.core.InputStreamProgressMonitor
-
- read(byte[], int, int) - Method in class moa.core.InputStreamProgressMonitor
-
- readBuffer(List<String>, List<String>, List<Measure>) - Method in class moa.gui.experimentertab.Stream
-
Read each algorithm file.
- readCollection(PreviewCollection<Preview>) - Method in class moa.gui.active.ALTaskTextViewerPanel
-
Parses a PreviewCollection and return the resulting
ParsedPreview object.
- readCSV(String) - Static method in class moa.gui.experimentertab.ReadFile
-
Allow to read a csv file.
- readCSV(String) - Method in class moa.gui.experimentertab.statisticaltests.StatisticalTest
-
Read a csv file from an path.
- readData() - Method in class moa.gui.experimentertab.statisticaltests.StatisticalTest
-
Read data from experiments sumaries.
- readData(String) - Method in class moa.gui.experimentertab.AnalyzeTab
-
Allows you to read the results file and update the corresponding fields.
- readData(String) - Method in class moa.gui.experimentertab.PlotTab
-
Allows to read the results file and update the corresponding fields.
- readData(String) - Method in class moa.gui.experimentertab.SummaryTab
-
Allows to read the results file and update the corresponding fields.
- ReadFile - Class in moa.gui.experimentertab
-
This class processes the results files of the algorithms in each directory.
- ReadFile(String) - Constructor for class moa.gui.experimentertab.ReadFile
-
File Constructor
- readFromFile(File) - Static method in class com.github.javacliparser.SerializeUtils
-
- readFromFile(File) - Static method in class moa.core.SerializeUtils
-
- readInstance() - Method in class com.yahoo.labs.samoa.instances.ArffLoader
-
Reads instance.
- readInstance(Reader) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Read instance.
- readInstanceDense() - Method in class com.yahoo.labs.samoa.instances.ArffLoader
-
Reads a dense instance from the file.
- readMinMaxDiffValues(HashSet<Integer>) - Method in class moa.streams.clustering.FileStream
-
- readNextInstanceFromFile() - Method in class moa.streams.ArffFileStream
-
- readNextInstanceFromFile() - Method in class moa.streams.clustering.FileStream
-
- readNextInstanceFromFile() - Method in class moa.streams.MultiTargetArffFileStream
-
- readProperties(String) - Static method in class moa.core.PropertiesReader
-
Reads properties that inherit from three locations.
- rearrangePoints(int[], int, int, int, double) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KMeansInpiredMethod
-
Re-arranges the indices array so that in the portion of the array
belonging to the node to be split, the points <= to the splitVal
are on the left of the portion and those > the splitVal are on the right.
- rearrangePoints(int[], int, int, int, double) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MidPointOfWidestDimension
-
Re-arranges the indices array such that the points <= to the splitVal
are on the left of the array and those > the splitVal are on the right.
- rearrangePoints(int[], int, int, int, double) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
-
Re-arranges the indices array such that the points <= to the splitVal
are on the left of the array and those > the splitVal are on the right.
- RebalanceStream - Class in moa.classifiers.meta.imbalanced
-
RebalanceStream
- RebalanceStream() - Constructor for class moa.classifiers.meta.imbalanced.RebalanceStream
-
- rebuild() - Method in class moa.clusterers.kmeanspm.BICO
-
If the number of ClusteringTreeNodes exceeds the maximum bound, the
global threshold T will be doubled and the tree will be rebuild with the
new threshold.
- recalculateData() - Method in class moa.clusterers.clustree.Entry
-
This functions reads every entry in the child node and calculates the
corresponding data Kernel.
- recalculateSTMErrorOption - Variable in class moa.classifiers.lazy.SAMkNN
-
- recall - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- recallPerClassOption - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- recentChunk - Variable in class moa.classifiers.meta.ADACC
-
Last chunk of data of size (tau_size) to compute the stability index
- RecommenderData - Interface in moa.recommender.data
-
- RecommenderData - Interface in moa.recommender.rc.data
-
- RecurrentConceptDriftStream - Class in moa.streams
-
Stream generator that adds recurrent concept drifts to examples in a stream.
- RecurrentConceptDriftStream() - Constructor for class moa.streams.RecurrentConceptDriftStream
-
- RedirectToDisplay() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
-
- RedirectToFile() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
-
- RedirectToFile(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
-
- redraw() - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- redraw() - Method in class moa.gui.visualization.RunVisualizer
-
- redrawOnResize() - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- RedrawPointLayer() - Method in class moa.gui.visualization.StreamOutlierPanel
-
- reEvalPeriodOption - Variable in class moa.classifiers.trees.EFDT
-
- reEvaluateBestSplit(EFDT.EFDTSplitNode, EFDT.EFDTSplitNode, int) - Method in class moa.classifiers.trees.EFDT.EFDTSplitNode
-
- refineOwners(KDTreeNode, Instances, int[]) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Refines the ownerlist.
- refresh() - Method in class moa.gui.EditableMultiChoiceOptionEditComponent
-
Refresh the shown contents.
- refresh() - Method in class moa.gui.experimentertab.ExpPreviewPanel
-
- refresh() - Method in class moa.gui.PreviewPanel
-
- refreshButton - Variable in class moa.gui.active.ALPreviewPanel
-
- refreshButton - Variable in class moa.gui.experimentertab.ExpPreviewPanel
-
- refreshButton - Variable in class moa.gui.PreviewPanel
-
- refreshVariedParamNameOption() - Method in class moa.options.DependentOptionsUpdater
-
Refresh the provided choices of an EditableMultiChoiceOption every time
a ClassOption (the prequential evaluation task) is changed.
- registerEditComponent(EditableMultiChoiceOptionEditComponent) - Method in class moa.options.EditableMultiChoiceOption
-
Register the corresponding UI component, so that it can be refreshed
when options have changed.
- REGRESSION - moa.gui.experimentertab.ExpPreviewPanel.TypePanel
-
- REGRESSION - moa.gui.PreviewPanel.TypePanel
-
- RegressionAccuracy - Class in moa.evaluation
-
- RegressionAccuracy() - Constructor for class moa.evaluation.RegressionAccuracy
-
- RegressionMainTask - Class in moa.tasks
-
Abstract Regression Main Task.
- RegressionMainTask() - Constructor for class moa.tasks.RegressionMainTask
-
- RegressionPerformanceEvaluator - Interface in moa.evaluation
-
Interface implemented by learner evaluators to monitor
the results of the regression learning process.
- RegressionTabPanel - Class in moa.gui
-
This panel allows the user to select and configure a task, and run it.
- RegressionTabPanel() - Constructor for class moa.gui.RegressionTabPanel
-
- RegressionTaskManagerPanel - Class in moa.gui
-
This panel displays the running tasks.
- RegressionTaskManagerPanel() - Constructor for class moa.gui.RegressionTaskManagerPanel
-
- RegressionTaskManagerPanel.ProgressCellRenderer - Class in moa.gui
-
- RegressionTaskManagerPanel.TaskTableModel - Class in moa.gui
-
- regressionTreeOption - Variable in class moa.classifiers.multilabel.trees.ISOUPTree
-
- regressionTreeOption - Variable in class moa.classifiers.trees.FIMTDD
-
- Regressor - Interface in moa.classifiers
-
Regressor interface for incremental regression models.
- Relation - Class in moa.gui.experimentertab.statisticaltests
-
T�tulo:
- Relation() - Constructor for class moa.gui.experimentertab.statisticaltests.Relation
-
- Relation(int, int) - Constructor for class moa.gui.experimentertab.statisticaltests.Relation
-
- relationName - Variable in class com.yahoo.labs.samoa.instances.InstanceInformation
-
The dataset's name.
- relativeLTMSizeOption - Variable in class moa.classifiers.lazy.SAMkNN
-
- RelativeMeanAbsoluteDeviationMT - Class in moa.classifiers.rules.multilabel.errormeasurers
-
Relative Mean Absolute Deviation for multitarget and with fading factor
- RelativeMeanAbsoluteDeviationMT() - Constructor for class moa.classifiers.rules.multilabel.errormeasurers.RelativeMeanAbsoluteDeviationMT
-
- RelativeRootMeanSquaredErrorMT - Class in moa.classifiers.rules.multilabel.errormeasurers
-
Relative Root Mean Squared Error for multitarget and with fading factor
- RelativeRootMeanSquaredErrorMT() - Constructor for class moa.classifiers.rules.multilabel.errormeasurers.RelativeRootMeanSquaredErrorMT
-
- ReLUFilter - Class in moa.streams.filters
-
- ReLUFilter() - Constructor for class moa.streams.filters.ReLUFilter
-
- remove() - Method in class moa.recommender.rc.data.impl.MemRecommenderData.RatingIterator
-
- remove() - Method in class moa.recommender.rc.utils.DenseVector.DenseVectorIterator
-
- remove() - Method in class moa.recommender.rc.utils.SparseVector.SparseVectorIterator
-
- remove(int) - Method in class moa.cluster.Clustering
-
remove a cluster from the clustering
- remove(int) - Method in class moa.core.AutoExpandVector
-
- remove(int) - Method in class moa.recommender.rc.utils.DenseVector
-
- remove(int) - Method in class moa.recommender.rc.utils.SparseVector
-
- remove(int) - Method in class moa.recommender.rc.utils.Vector
-
- remove(DATA) - Method in class moa.clusterers.outliers.utils.mtree.MTree
-
Removes a data object from the M-Tree.
- remove(Object) - Method in class moa.core.AutoExpandVector
-
- remove(CFCluster) - Method in class moa.clusterers.macro.NonConvexCluster
-
- Remove(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.AbstractC.ISBIndex
-
- Remove(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.Angiulli.ISBIndex
-
- Remove(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.ISBIndex
-
- Remove(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex
-
- removeAll() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- removeAllOptions() - Method in class com.github.javacliparser.Options
-
- removeAttributesOption - Variable in class moa.streams.clustering.FileStream
-
- removeBadSplits(SplitCriterion, double, double, double) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
-
A method to remove all nodes in the E-BST in which it and all it's
children represent 'bad' split points
- removeBlock(SEEDChangeDetector.SEEDBlock) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- removeChangeListener(ChangeListener) - Method in class com.github.javacliparser.gui.ClassOptionEditComponent
-
Removes the listener from the internal set of listeners.
- removeChangeListener(ChangeListener) - Method in class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
Removes the listener from the internal set of listeners.
- removeChild(Iadem2.Node) - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- removeClusterChangeListener(ClusterEventListener) - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
Remove a listener
- RemoveDiscreteAttributeFilter - Class in moa.streams.filters
-
Filter for removing discrete attributes in instances of a stream.
- RemoveDiscreteAttributeFilter() - Constructor for class moa.streams.filters.RemoveDiscreteAttributeFilter
-
- removeElementAt(int) - Method in class moa.core.FastVector
-
Deletes an element from this vector.
- removeExcessTrees() - Method in class moa.classifiers.trees.ORTO
-
- removeExperts() - Method in class moa.classifiers.meta.DynamicWeightedMajority
-
- RemoveExpiredOutlier(MyBaseOutlierDetector.Outlier) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- removeFirstBlock() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- removeGrid(DensityGrid) - Method in class moa.clusterers.dstream.GridCluster
-
- removeItem(int) - Method in class moa.recommender.rc.data.AbstractRecommenderData
-
- removeItem(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- removeItem(int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- RemoveNode(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.MicroCluster
-
- removeObject(int) - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- removeOption(Option) - Method in class com.github.javacliparser.Options
-
- removeOption(String) - Method in class com.github.javacliparser.Options
-
- RemoveOutlier(MyBaseOutlierDetector.Outlier) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- removePoorAttsOption - Variable in class moa.classifiers.trees.EFDT
-
- removePoorAttsOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- removePoorAttsOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- removePoorestModelBytes() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Removes the poorest classifier from the model, thus decreasing the models
size.
- removePoorestModelBytes() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- RemovePrecNeigh(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- RemovePrecNeigh(ISBIndex.ISBNode) - Method in class moa.clusterers.outliers.SimpleCOD.ISBIndex.ISBNode
-
- removePropertyChangeListener(PropertyChangeListener) - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Removes a PropertyChangeListener.
- removeRange(int, int) - Method in class moa.core.AutoExpandVector
-
- removeRating(int, int) - Method in class moa.recommender.rc.data.AbstractRecommenderData
-
- removeRating(int, int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- removeRating(int, int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- removeSubstring(String, String) - Static method in class moa.core.Utils
-
Removes all occurrences of a string from another string.
- removeSubtree(Iadem3Subtree) - Method in class moa.classifiers.trees.iadem.Iadem3
-
- removeSubtree(Iadem3Subtree) - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- removeTaskCompletionListener(TaskCompletionListener) - Method in class moa.gui.experimentertab.ExpTaskThread
-
- removeTaskCompletionListener(TaskCompletionListener) - Method in class moa.tasks.TaskThread
-
- removeUser(int) - Method in class moa.recommender.rc.data.AbstractRecommenderData
-
- removeUser(int) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- removeUser(int) - Method in interface moa.recommender.rc.data.RecommenderData
-
- removeWeakestExpert(int) - Method in class moa.classifiers.meta.DynamicWeightedMajority
-
- renderAlgoPanel() - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- renderAlgoPanel() - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- renderAWTBox(Graphics, int, int, int, int) - Method in interface moa.gui.AWTRenderer
-
- repaint() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- repaint() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- repaintOutliers() - Method in class moa.gui.visualization.StreamOutlierPanel
-
- replaceSubstring(String, String, String) - Static method in class moa.core.Utils
-
Replaces with a new string, all occurrences of a string from
another string.
- ReplacingMissingValuesFilter - Class in moa.streams.filters
-
Replaces the missing values with another value according to the selected
strategy.
- ReplacingMissingValuesFilter() - Constructor for class moa.streams.filters.ReplacingMissingValuesFilter
-
- ReplacingMissingValuesFilter.MapUtil - Class in moa.streams.filters
-
- replicatesOption - Variable in class moa.classifiers.core.statisticaltests.Cramer
-
- repository - Variable in class moa.gui.experimentertab.ExpTaskThread
-
- repository - Variable in class moa.tasks.TaskThread
-
- Repository(int) - Constructor for class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Repository
-
- requestCancel() - Method in class moa.tasks.NullMonitor
-
- requestCancel() - Method in class moa.tasks.StandardTaskMonitor
-
- requestCancel() - Method in interface moa.tasks.TaskMonitor
-
Requests the task monitored to cancel.
- requestPause() - Method in class moa.tasks.NullMonitor
-
- requestPause() - Method in class moa.tasks.StandardTaskMonitor
-
- requestPause() - Method in interface moa.tasks.TaskMonitor
-
Requests the task monitored to pause.
- requestResultPreview() - Method in class moa.tasks.NullMonitor
-
- requestResultPreview() - Method in class moa.tasks.StandardTaskMonitor
-
- requestResultPreview() - Method in interface moa.tasks.TaskMonitor
-
Requests to preview the task result.
- requestResultPreview(ResultPreviewListener) - Method in class moa.tasks.NullMonitor
-
- requestResultPreview(ResultPreviewListener) - Method in class moa.tasks.StandardTaskMonitor
-
- requestResultPreview(ResultPreviewListener) - Method in interface moa.tasks.TaskMonitor
-
Requests to preview the task result.
- requestResume() - Method in class moa.tasks.NullMonitor
-
- requestResume() - Method in class moa.tasks.StandardTaskMonitor
-
- requestResume() - Method in interface moa.tasks.TaskMonitor
-
Requests the task monitored to resume.
- RequiredOptionNotSpecifiedException - Exception in moa.options
-
- RequiredOptionNotSpecifiedException() - Constructor for exception moa.options.RequiredOptionNotSpecifiedException
-
- requiredType - Variable in class com.github.javacliparser.AbstractClassOption
-
The class type
- requiredType - Variable in class moa.options.AbstractClassOption
-
The class type
- Reservoir(int, int) - Constructor for class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Reservoir
-
- reset - Variable in class moa.classifiers.bayes.NaiveBayesMultinomial
-
- reset - Variable in class moa.classifiers.functions.Perceptron
-
- reset - Variable in class moa.classifiers.meta.LimAttClassifier
-
- reset - Variable in class moa.classifiers.rules.RuleClassification
-
- reset - Variable in class moa.classifiers.trees.ARFFIMTDD.FIMTDDPerceptron
-
- reset - Variable in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
-
- reset() - Method in class moa.classifiers.functions.SGD
-
Reset the classifier.
- reset() - Method in class moa.classifiers.functions.SGDMultiClass
-
Reset the classifier.
- reset() - Method in class moa.classifiers.functions.SPegasos
-
Reset the classifier.
- reset() - Method in class moa.classifiers.meta.AdaptiveRandomForest.ARFBaseLearner
-
- reset() - Method in class moa.classifiers.meta.AdaptiveRandomForestRegressor.ARFFIMTDDBaseLearner
-
- reset() - Method in class moa.classifiers.meta.LimAttClassifier.CombinationGenerator
-
- reset() - Method in class moa.classifiers.rules.driftdetection.PageHinkleyFading
-
- reset() - Method in class moa.classifiers.rules.driftdetection.PageHinkleyTest
-
- reset() - Method in class moa.classifiers.rules.functions.Perceptron
-
- reset() - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- reset() - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- reset() - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- reset() - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- reset() - Method in class moa.core.InputStreamProgressMonitor
-
- reset() - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator
-
- reset() - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- reset() - Method in class moa.evaluation.BasicConceptDriftPerformanceEvaluator
-
- reset() - Method in class moa.evaluation.BasicMultiLabelPerformanceEvaluator
-
- reset() - Method in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- reset() - Method in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- reset() - Method in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- reset() - Method in interface moa.evaluation.LearningPerformanceEvaluator
-
Resets this evaluator.
- reset() - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- reset() - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- reset() - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator
-
- reset() - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- reset() - Method in interface moa.recommender.dataset.Dataset
-
- reset() - Method in class moa.recommender.dataset.impl.FlixsterDataset
-
- reset() - Method in class moa.recommender.dataset.impl.JesterDataset
-
- reset() - Method in class moa.recommender.dataset.impl.MovielensDataset
-
- reset(double, double) - Method in class moa.classifiers.rules.functions.TargetMean
-
- reset(int) - Method in class moa.evaluation.ALWindowClassificationPerformanceEvaluator
-
- reset(int) - Method in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator
-
- reset(int) - Method in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- reset(int) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- reset(int) - Method in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- reset(int) - Method in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator
-
- reset(int) - Method in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- reset(Instance, long, Random) - Method in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- resetBatch - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- resetBatchMajority - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- resetBatchMinority - Variable in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- resetButton - Variable in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- resetChange() - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- resetError() - Method in class moa.classifiers.rules.functions.Perceptron
-
- resetError() - Method in class moa.classifiers.rules.functions.TargetMean
-
- resetFF() - Method in class moa.classifiers.trees.ORTO.OptionNode
-
- resetLearning() - Method in class moa.classifiers.AbstractClassifier
-
- resetLearning() - Method in interface moa.classifiers.active.budget.BudgetManager
-
Resets the budget manager.
- resetLearning() - Method in class moa.classifiers.active.budget.FixedBM
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.AbstractChangeDetector
-
Resets this change detector.
- resetLearning() - Method in class moa.classifiers.core.driftdetection.ADWINChangeDetector
-
- resetLearning() - Method in interface moa.classifiers.core.driftdetection.ChangeDetector
-
Resets this change detector.
- resetLearning() - Method in class moa.classifiers.core.driftdetection.CusumDM
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.DDM
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.EDDM
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.EnsembleDriftDetectionMethods
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.EWMAChartDM
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.GeometricMovingAverageDM
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.HDDM_A_Test
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.PageHinkleyDM
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.RDDM
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
-
- resetLearning() - Method in class moa.classifiers.core.driftdetection.STEPD
-
- resetLearning() - Method in class moa.classifiers.rules.core.changedetection.NoChangeDetection
-
- resetLearning() - Method in class moa.clusterers.AbstractClusterer
-
- resetLearning() - Method in interface moa.clusterers.Clusterer
-
- resetLearning() - Method in class moa.clusterers.outliers.AnyOut.AnyOutCore
-
- resetLearning() - Method in interface moa.learners.Learner
-
Resets this learner.
- resetLearningImpl() - Method in class moa.classifiers.AbstractClassifier
-
Resets this classifier.
- resetLearningImpl() - Method in class moa.classifiers.active.ALRandom
-
- resetLearningImpl() - Method in class moa.classifiers.active.ALUncertainty
-
- resetLearningImpl() - Method in class moa.classifiers.bayes.NaiveBayes
-
- resetLearningImpl() - Method in class moa.classifiers.bayes.NaiveBayesMultinomial
-
- resetLearningImpl() - Method in class moa.classifiers.drift.DriftDetectionMethodClassifier
-
- resetLearningImpl() - Method in class moa.classifiers.functions.AdaGrad
-
- resetLearningImpl() - Method in class moa.classifiers.functions.MajorityClass
-
- resetLearningImpl() - Method in class moa.classifiers.functions.NoChange
-
- resetLearningImpl() - Method in class moa.classifiers.functions.Perceptron
-
- resetLearningImpl() - Method in class moa.classifiers.functions.SGD
-
- resetLearningImpl() - Method in class moa.classifiers.functions.SGDMultiClass
-
- resetLearningImpl() - Method in class moa.classifiers.functions.SPegasos
-
- resetLearningImpl() - Method in class moa.classifiers.lazy.kNN
-
- resetLearningImpl() - Method in class moa.classifiers.lazy.kNNwithPAW
-
- resetLearningImpl() - Method in class moa.classifiers.lazy.kNNwithPAWandADWIN
-
- resetLearningImpl() - Method in class moa.classifiers.lazy.SAMkNN
-
- resetLearningImpl() - Method in class moa.classifiers.meta.AccuracyUpdatedEnsemble
-
- resetLearningImpl() - Method in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- resetLearningImpl() - Method in class moa.classifiers.meta.AdaptiveRandomForest
-
- resetLearningImpl() - Method in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- resetLearningImpl() - Method in class moa.classifiers.meta.ADOB
-
- resetLearningImpl() - Method in class moa.classifiers.meta.BOLE
-
- resetLearningImpl() - Method in class moa.classifiers.meta.DACC
-
- resetLearningImpl() - Method in class moa.classifiers.meta.DynamicWeightedMajority
-
- resetLearningImpl() - Method in class moa.classifiers.meta.HeterogeneousEnsembleBlast
-
- resetLearningImpl() - Method in class moa.classifiers.meta.HeterogeneousEnsembleBlastFadingFactors
-
- resetLearningImpl() - Method in class moa.classifiers.meta.imbalanced.CSMOTE
-
- resetLearningImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineAdaBoost
-
- resetLearningImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineAdaC2
-
- resetLearningImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineCSB2
-
- resetLearningImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- resetLearningImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- resetLearningImpl() - Method in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- resetLearningImpl() - Method in class moa.classifiers.meta.imbalanced.RebalanceStream
-
- resetLearningImpl() - Method in class moa.classifiers.meta.LearnNSE
-
- resetLearningImpl() - Method in class moa.classifiers.meta.LeveragingBag
-
- resetLearningImpl() - Method in class moa.classifiers.meta.LimAttClassifier
-
- resetLearningImpl() - Method in class moa.classifiers.meta.OCBoost
-
- resetLearningImpl() - Method in class moa.classifiers.meta.OnlineAccuracyUpdatedEnsemble
-
- resetLearningImpl() - Method in class moa.classifiers.meta.OnlineSmoothBoost
-
- resetLearningImpl() - Method in class moa.classifiers.meta.OzaBag
-
- resetLearningImpl() - Method in class moa.classifiers.meta.OzaBagAdwin
-
- resetLearningImpl() - Method in class moa.classifiers.meta.OzaBagASHT
-
- resetLearningImpl() - Method in class moa.classifiers.meta.OzaBoost
-
- resetLearningImpl() - Method in class moa.classifiers.meta.OzaBoostAdwin
-
- resetLearningImpl() - Method in class moa.classifiers.meta.PairedLearners
-
- resetLearningImpl() - Method in class moa.classifiers.meta.RandomRules
-
- resetLearningImpl() - Method in class moa.classifiers.meta.RCD
-
- resetLearningImpl() - Method in class moa.classifiers.meta.StreamingRandomPatches
-
- resetLearningImpl() - Method in class moa.classifiers.meta.TemporallyAugmentedClassifier
-
- resetLearningImpl() - Method in class moa.classifiers.meta.WeightedMajorityAlgorithm
-
- resetLearningImpl() - Method in class moa.classifiers.meta.WEKAClassifier
-
- resetLearningImpl() - Method in class moa.classifiers.multilabel.MajorityLabelset
-
- resetLearningImpl() - Method in class moa.classifiers.multilabel.MEKAClassifier
-
- resetLearningImpl() - Method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- resetLearningImpl() - Method in class moa.classifiers.multitarget.BasicMultiLabelLearner
-
- resetLearningImpl() - Method in class moa.classifiers.multitarget.BasicMultiTargetRegressor
-
- resetLearningImpl() - Method in class moa.classifiers.multitarget.functions.MultiTargetNoChange
-
- resetLearningImpl() - Method in class moa.classifiers.oneclass.Autoencoder
-
Marks the autoencoder as needing to be reinitialized.
- resetLearningImpl() - Method in class moa.classifiers.oneclass.HSTrees
-
Reset the classifier's parameters and data structures.
- resetLearningImpl() - Method in class moa.classifiers.oneclass.NearestNeighbourDescription
-
Resets the implementation's parameters and data structures.
- resetLearningImpl() - Method in class moa.classifiers.rules.AbstractAMRules
-
- resetLearningImpl() - Method in class moa.classifiers.rules.AMRulesRegressorOld
-
This method initializes and resets the algorithm.
- resetLearningImpl() - Method in class moa.classifiers.rules.BinaryClassifierFromRegressor
-
- resetLearningImpl() - Method in class moa.classifiers.rules.functions.AdaptiveNodePredictor
-
- resetLearningImpl() - Method in class moa.classifiers.rules.functions.FadingTargetMean
-
- resetLearningImpl() - Method in class moa.classifiers.rules.functions.LowPassFilteredLearner
-
- resetLearningImpl() - Method in class moa.classifiers.rules.functions.Perceptron
-
A method to reset the model
- resetLearningImpl() - Method in class moa.classifiers.rules.functions.TargetMean
-
- resetLearningImpl() - Method in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- resetLearningImpl() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- resetLearningImpl() - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- resetLearningImpl() - Method in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- resetLearningImpl() - Method in class moa.classifiers.rules.multilabel.functions.DominantLabelsClassifier
-
- resetLearningImpl() - Method in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- resetLearningImpl() - Method in class moa.classifiers.rules.multilabel.meta.MultiLabelRandomAMRules
-
- resetLearningImpl() - Method in class moa.classifiers.rules.RuleClassifier
-
- resetLearningImpl() - Method in class moa.classifiers.trees.ARFFIMTDD
-
- resetLearningImpl() - Method in class moa.classifiers.trees.ASHoeffdingTree
-
- resetLearningImpl() - Method in class moa.classifiers.trees.DecisionStump
-
- resetLearningImpl() - Method in class moa.classifiers.trees.EFDT
-
- resetLearningImpl() - Method in class moa.classifiers.trees.FIMTDD
-
- resetLearningImpl() - Method in class moa.classifiers.trees.HoeffdingOptionTree
-
- resetLearningImpl() - Method in class moa.classifiers.trees.HoeffdingTree
-
- resetLearningImpl() - Method in class moa.classifiers.trees.iadem.Iadem2
-
- resetLearningImpl() - Method in class moa.classifiers.trees.ORTO
-
- resetLearningImpl() - Method in class moa.clusterers.AbstractClusterer
-
- resetLearningImpl() - Method in class moa.clusterers.ClusterGenerator
-
- resetLearningImpl() - Method in class moa.clusterers.clustream.Clustream
-
- resetLearningImpl() - Method in class moa.clusterers.clustream.WithKmeans
-
- resetLearningImpl() - Method in class moa.clusterers.clustree.ClusTree
-
- resetLearningImpl() - Method in class moa.clusterers.CobWeb
-
- resetLearningImpl() - Method in class moa.clusterers.denstream.WithDBSCAN
-
- resetLearningImpl() - Method in class moa.clusterers.dstream.Dstream
-
- resetLearningImpl() - Method in class moa.clusterers.kmeanspm.BICO
-
- resetLearningImpl() - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- resetLearningImpl() - Method in class moa.clusterers.outliers.AnyOut.AnyOut
-
- resetLearningImpl() - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- resetLearningImpl() - Method in class moa.clusterers.streamkm.StreamKM
-
- resetLearningImpl() - Method in class moa.clusterers.WekaClusteringAlgorithm
-
- resetLearningImpl() - Method in class moa.learners.ChangeDetectorLearner
-
- resetLearningImpl() - Method in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- resetLearningImpl() - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTree
-
- resetLearningImpl() - Method in class moa.learners.featureanalysis.FeatureImportanceHoeffdingTreeEnsemble
-
- resetToDefault() - Method in class com.github.javacliparser.AbstractOption
-
- resetToDefault() - Method in interface com.github.javacliparser.Option
-
Resets this option to the default value
- resetToDefaults() - Method in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- resetToDefaults() - Method in class com.github.javacliparser.Options
-
- resetTree - Variable in class moa.classifiers.trees.ASHoeffdingTree
-
- resetTreesOption - Variable in class moa.classifiers.meta.OzaBagASHT
-
- resetVariablesAtDrift() - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveNominalVirtualNode
-
- resetVariablesAtDrift() - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveNumericVirtualNode
-
- resetVariablesAtDrift() - Method in interface moa.classifiers.trees.iadem.Iadem3.restartsVariablesAtDrift
-
- resetWithMemory() - Method in class moa.classifiers.rules.multilabel.functions.AbstractAMRulesFunctionBasicMlLearner
-
- resetWithMemory() - Method in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- resetWithMemory() - Method in interface moa.classifiers.rules.multilabel.functions.AMRulesFunction
-
- resetWithMemory() - Method in class moa.classifiers.rules.multilabel.functions.DominantLabelsClassifier
-
- resetWithMemory() - Method in class moa.classifiers.rules.multilabel.functions.MultiLabelNaiveBayes
-
- resetWithMemory() - Method in class moa.classifiers.rules.multilabel.functions.MultiLabelPerceptronClassification
-
- resetWithMemory() - Method in class moa.classifiers.rules.multilabel.functions.MultiTargetMeanRegressor
-
- resetWithMemory() - Method in class moa.classifiers.rules.multilabel.functions.MultiTargetPerceptronRegressor
-
- resetWithMemory() - Method in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- resizeTree(HoeffdingTree.Node, int) - Method in class moa.classifiers.trees.ASHoeffdingTree
-
- restart() - Method in class moa.streams.ArffFileStream
-
- restart() - Method in class moa.streams.BootstrappedStream
-
- restart() - Method in class moa.streams.CachedInstancesStream
-
- restart() - Method in class moa.streams.clustering.FileStream
-
- restart() - Method in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- restart() - Method in class moa.streams.clustering.SimpleCSVStream
-
- restart() - Method in class moa.streams.ConceptDriftRealStream
-
- restart() - Method in class moa.streams.ConceptDriftStream
-
- restart() - Method in interface moa.streams.ExampleStream
-
Restarts this stream.
- restart() - Method in class moa.streams.FilteredStream
-
- restart() - Method in class moa.streams.filters.AbstractMultiLabelStreamFilter
-
- restart() - Method in class moa.streams.filters.AbstractStreamFilter
-
- restart() - Method in class moa.streams.generators.AgrawalGenerator
-
- restart() - Method in class moa.streams.generators.AssetNegotiationGenerator
-
- restart() - Method in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- restart() - Method in class moa.streams.generators.HyperplaneGenerator
-
- restart() - Method in class moa.streams.generators.LEDGenerator
-
- restart() - Method in class moa.streams.generators.MixedGenerator
-
- restart() - Method in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- restart() - Method in class moa.streams.generators.RandomRBFGenerator
-
- restart() - Method in class moa.streams.generators.RandomTreeGenerator
-
- restart() - Method in class moa.streams.generators.SEAGenerator
-
- restart() - Method in class moa.streams.generators.SineGenerator
-
- restart() - Method in class moa.streams.generators.STAGGERGenerator
-
- restart() - Method in class moa.streams.generators.TextGenerator
-
- restart() - Method in class moa.streams.generators.WaveformGenerator
-
- restart() - Method in class moa.streams.ImbalancedStream
-
- restart() - Method in class moa.streams.IrrelevantFeatureAppenderStream
-
- restart() - Method in class moa.streams.MultiFilteredStream
-
- restart() - Method in class moa.streams.MultiLabelFilteredStream
-
- restart() - Method in class moa.streams.MultiTargetArffFileStream
-
- restart() - Method in class moa.streams.PartitioningStream
-
- restartAtDrift - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- restartChangeDetection() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- restartChangeDetection() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- restartChangeDetection() - Method in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- restartChangeDetection() - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- restartChangeDetection() - Method in class moa.classifiers.trees.FIMTDD.InnerNode
-
- restartChangeDetection() - Method in class moa.classifiers.trees.FIMTDD.Node
-
- restartImpl() - Method in class moa.streams.filters.AbstractMultiLabelStreamFilter
-
Restarts this filter.
- restartImpl() - Method in class moa.streams.filters.AbstractStreamFilter
-
Restarts this filter.
- restartImpl() - Method in class moa.streams.filters.AddNoiseFilter
-
- restartImpl() - Method in class moa.streams.filters.RBFFilter
-
- restartImpl() - Method in class moa.streams.filters.ReLUFilter
-
- restartImpl() - Method in class moa.streams.filters.RemoveDiscreteAttributeFilter
-
- restartImpl() - Method in class moa.streams.filters.ReplacingMissingValuesFilter
-
- restartImpl() - Method in class moa.streams.filters.SelectAttributesFilter
-
- restartVariablesAtDrift() - Method in class moa.classifiers.trees.iadem.Iadem3.AdaptiveLeafNode
-
- resultingClassDistributionFromSplit(int) - Method in class moa.classifiers.core.AttributeSplitSuggestion
-
- resultingClassDistributions - Variable in class moa.classifiers.core.AttributeSplitSuggestion
-
- resultingNodeStatistics - Variable in class moa.classifiers.rules.multilabel.core.AttributeExpansionSuggestion
-
- resultKnownForInstance(Instance) - Method in class moa.classifiers.core.conditionaltests.InstanceConditionalTest
-
Gets whether the number of the branch for an instance is known.
- resultPreviewer - Variable in class moa.tasks.StandardTaskMonitor
-
- ResultPreviewListener - Interface in moa.tasks
-
Interface implemented by classes that preview results
on the Graphical User Interface
- resultPreviewRequested - Variable in class moa.tasks.StandardTaskMonitor
-
- resultPreviewRequested() - Method in class moa.tasks.NullMonitor
-
- resultPreviewRequested() - Method in class moa.tasks.StandardTaskMonitor
-
- resultPreviewRequested() - Method in interface moa.tasks.TaskMonitor
-
Gets whether there is a request for preview the task result.
- resultsPath - Variable in class moa.gui.experimentertab.SummaryViewer
-
- resultsPath - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- resume() - Static method in class moa.gui.visualization.RunOutlierVisualizer
-
- resume() - Static method in class moa.gui.visualization.RunVisualizer
-
- resumeSelectedTasks() - Method in class moa.gui.active.ALTaskManagerPanel
-
- resumeSelectedTasks() - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- resumeSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- resumeSelectedTasks() - Method in class moa.gui.experimentertab.TaskManagerTabPanel
-
Reseme task
- resumeSelectedTasks() - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- resumeSelectedTasks() - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- resumeSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
-
- resumeSelectedTasks() - Method in class moa.gui.TaskManagerPanel
-
- resumeTask() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- resumeTask() - Method in class moa.tasks.meta.ALTaskThread
-
- resumeTask() - Method in class moa.tasks.TaskThread
-
- resumeTaskButton - Variable in class moa.gui.active.ALTaskManagerPanel
-
- resumeTaskButton - Variable in class moa.gui.AuxiliarTaskManagerPanel
-
- resumeTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- resumeTaskButton - Variable in class moa.gui.MultiLabelTaskManagerPanel
-
- resumeTaskButton - Variable in class moa.gui.MultiTargetTaskManagerPanel
-
- resumeTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
-
- resumeTaskButton - Variable in class moa.gui.TaskManagerPanel
-
- revalidate() - Method in class moa.gui.active.ALTaskManagerPanel.ProgressCellRenderer
-
- revalidate() - Method in class moa.gui.AuxiliarTaskManagerPanel.ProgressCellRenderer
-
- revalidate() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel.ProgressCellRenderer
-
- revalidate() - Method in class moa.gui.experimentertab.TaskManagerTabPanel.ProgressCellRenderer
-
- revalidate() - Method in class moa.gui.MultiLabelTaskManagerPanel.ProgressCellRenderer
-
- revalidate() - Method in class moa.gui.MultiTargetTaskManagerPanel.ProgressCellRenderer
-
- revalidate() - Method in class moa.gui.RegressionTaskManagerPanel.ProgressCellRenderer
-
- revalidate() - Method in class moa.gui.TaskManagerPanel.ProgressCellRenderer
-
- revertNewLines(String) - Static method in class moa.core.Utils
-
Reverts \r and \n in a string into carriage returns and new lines.
- rFactor - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- rFactorOption - Variable in class moa.recommender.predictor.BRISMFPredictor
-
- right - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver.Node
-
- right - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression.Node
-
- right - Variable in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
-
- RIGHT_INSIDE - moa.tasks.Plot.LegendLocation
-
- RIGHT_OUTSIDE - moa.tasks.Plot.LegendLocation
-
- rightStatistics - Variable in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver.Node
-
- rightStatistics - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- rightStatistics - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- Rmc - Variable in class moa.clusterers.outliers.MCOD.ISBIndex.ISBNode
-
- rnd - Variable in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- root - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
-
- root - Variable in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
-
- root - Variable in class moa.classifiers.rules.core.attributeclassobservers.FIMTDDNumericAttributeClassLimitObserver.Node
-
- root - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- root - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- root - Variable in class moa.clusterers.clustree.ClusTree
-
The root node of the tree.
- root - Variable in class moa.clusterers.outliers.utils.mtree.MTree
-
- root1 - Variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
-
- RootMeanSquaredError - Class in moa.classifiers.rules.errormeasurers
-
Computes the Root Mean Squared Error for single target regression problems
- RootMeanSquaredError() - Constructor for class moa.classifiers.rules.errormeasurers.RootMeanSquaredError
-
- RootMeanSquaredErrorMT - Class in moa.classifiers.rules.multilabel.errormeasurers
-
Root Mean Squared Error for multitarget and with fading factor
- RootMeanSquaredErrorMT() - Constructor for class moa.classifiers.rules.multilabel.errormeasurers.RootMeanSquaredErrorMT
-
- round(double) - Method in class moa.classifiers.rules.RuleClassifier
-
- round(double) - Static method in class moa.core.Utils
-
Rounds a double to the next nearest integer value.
- round(double) - Method in class moa.gui.experimentertab.TaskTextViewerPanel
-
- round(double) - Method in class moa.gui.TaskTextViewerPanel
-
- roundDouble(double, int) - Static method in class moa.core.Utils
-
Rounds a double to the given number of decimal places.
- rowKappa - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- rowKappa - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator
-
- rowKappa - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- rp - Variable in class moa.recommender.predictor.BaselinePredictor
-
- rp - Variable in class moa.recommender.predictor.BRISMFPredictor
-
- Rule - Class in moa.classifiers.rules.core
-
- Rule(Rule.Builder) - Constructor for class moa.classifiers.rules.core.Rule
-
- Rule.Builder - Class in moa.classifiers.rules.core
-
- RuleActiveLearningNode - Class in moa.classifiers.rules.core
-
A modified ActiveLearningNode that uses a Perceptron as the leaf node model,
and ensures that the class values sent to the attribute observers are not
truncated to ints if regression is being performed
- RuleActiveLearningNode() - Constructor for class moa.classifiers.rules.core.RuleActiveLearningNode
-
- RuleActiveLearningNode(double[]) - Constructor for class moa.classifiers.rules.core.RuleActiveLearningNode
-
Create a new RuleActiveLearningNode
- RuleActiveLearningNode(Rule.Builder) - Constructor for class moa.classifiers.rules.core.RuleActiveLearningNode
-
- RuleActiveRegressionNode - Class in moa.classifiers.rules.core
-
A modified ActiveLearningNode that uses a Perceptron as the leaf node model,
and ensures that the class values sent to the attribute observers are not
truncated to ints if regression is being performed
- RuleActiveRegressionNode() - Constructor for class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- RuleActiveRegressionNode(double[]) - Constructor for class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- RuleActiveRegressionNode(Rule.Builder) - Constructor for class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- ruleAnomaliesIndex - Variable in class moa.classifiers.rules.RuleClassifier
-
- ruleAnomaliesIndexSupervised - Variable in class moa.classifiers.rules.RuleClassifier
-
- ruleAttribAnomalyStatistics - Variable in class moa.classifiers.rules.RuleClassifier
-
- ruleAttribAnomalyStatisticsSupervised - Variable in class moa.classifiers.rules.RuleClassifier
-
- RuleClassification - Class in moa.classifiers.rules
-
- RuleClassification() - Constructor for class moa.classifiers.rules.RuleClassification
-
- RuleClassification(RuleClassification) - Constructor for class moa.classifiers.rules.RuleClassification
-
- RuleClassifier - Class in moa.classifiers.rules
-
This classifier learn ordered and unordered rule set from data stream.
- RuleClassifier() - Constructor for class moa.classifiers.rules.RuleClassifier
-
- RuleClassifierNBayes - Class in moa.classifiers.rules
-
This classifier learn ordered and unordered rule set from data stream with naive Bayes learners.
- RuleClassifierNBayes() - Constructor for class moa.classifiers.rules.RuleClassifierNBayes
-
- ruleClassIndex - Variable in class moa.classifiers.rules.RuleClassifier
-
- ruleEvaluate(Instance) - Method in class moa.classifiers.rules.RuleClassification
-
- RuleExpandedMessage - Class in moa.classifiers.rules.featureranking.messages
-
- RuleExpandedMessage(int) - Constructor for class moa.classifiers.rules.featureranking.messages.RuleExpandedMessage
-
- RuleExpandedMessage(int, boolean) - Constructor for class moa.classifiers.rules.featureranking.messages.RuleExpandedMessage
-
- ruleInformation - Variable in class moa.classifiers.rules.featureranking.BasicFeatureRanking
-
- ruleInformation - Variable in class moa.classifiers.rules.featureranking.MeritFeatureRanking
-
- ruleInformation - Variable in class moa.classifiers.rules.featureranking.WeightedMajorityFeatureRanking
-
- RuleInformation() - Constructor for class moa.classifiers.rules.featureranking.BasicFeatureRanking.RuleInformation
-
- RuleInformation() - Constructor for class moa.classifiers.rules.featureranking.MeritFeatureRanking.RuleInformation
-
- RuleInformation(int) - Constructor for class moa.classifiers.rules.featureranking.WeightedMajorityFeatureRanking.RuleInformation
-
- ruleNumberID - Variable in class moa.classifiers.rules.AbstractAMRules
-
- ruleNumberID - Variable in class moa.classifiers.rules.core.Rule
-
- ruleNumberID - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- ruleNumberID - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- ruleNumberID - Variable in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- ruleSet - Variable in class moa.classifiers.rules.AbstractAMRules
-
- ruleSet - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- ruleSet - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- ruleSet - Variable in class moa.classifiers.rules.RuleClassifier
-
- RuleSet - Class in moa.classifiers.rules.core
-
- RuleSet() - Constructor for class moa.classifiers.rules.core.RuleSet
-
- ruleSetAnomalies - Variable in class moa.classifiers.rules.RuleClassifier
-
- ruleSetAnomaliesSupervised - Variable in class moa.classifiers.rules.RuleClassifier
-
- RuleSplitNode - Class in moa.classifiers.rules.core
-
A modified SplitNode method implementing the extra information
- RuleSplitNode(InstanceConditionalTest, double[]) - Constructor for class moa.classifiers.rules.core.RuleSplitNode
-
Create a new RuleSplitNode
- run() - Method in class moa.classifiers.meta.AdaptiveRandomForest.TrainingRunnable
-
- run() - Method in class moa.clusterers.meta.EnsembleClustererAbstract.EnsembleRunnable
-
- run() - Method in class moa.gui.BatchCmd
-
- run() - Method in class moa.gui.experimentertab.ExpTaskThread
-
- run() - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- run() - Method in class moa.gui.visualization.RunVisualizer
-
- run() - Method in class moa.tasks.meta.ALTaskThread
-
- run() - Method in class moa.tasks.TaskThread
-
- runBatch(ClusteringStream, AbstractClusterer, boolean[], int, String) - Static method in class moa.gui.BatchCmd
-
- runConfig - Variable in class moa.tasks.WriteConfigurationToJupyterNotebook
-
- RUNNING - moa.gui.experimentertab.ExpTaskThread.Status
-
- RUNNING - moa.tasks.TaskThread.Status
-
- runningTask - Variable in class moa.gui.experimentertab.ExpTaskThread
-
- runningTask - Variable in class moa.tasks.TaskThread
-
- RunOutlierVisualizer - Class in moa.gui.visualization
-
- RunOutlierVisualizer(OutlierVisualTab, OutlierSetupTab) - Constructor for class moa.gui.visualization.RunOutlierVisualizer
-
- runSeed - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- RunStreamTasks - Class in moa.tasks
-
Task for running several experiments modifying values of parameters.
- RunStreamTasks() - Constructor for class moa.tasks.RunStreamTasks
-
- runTask() - Method in class moa.gui.experimentertab.TaskManagerTabPanel
-
Executes the Task
- runTask(ALMainTask) - Method in class moa.gui.active.ALTaskManagerPanel
-
- runTask(Task) - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- runTask(Task) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- runTask(Task) - Method in class moa.gui.featureanalysis.FeatureImportancePanel
-
- runTask(Task) - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- runTask(Task) - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- runTask(Task) - Method in class moa.gui.RegressionTaskManagerPanel
-
- runTask(Task) - Method in class moa.gui.TaskManagerPanel
-
- runTaskButton - Variable in class moa.gui.active.ALTaskManagerPanel
-
- runTaskButton - Variable in class moa.gui.AuxiliarTaskManagerPanel
-
- runTaskButton - Variable in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- runTaskButton - Variable in class moa.gui.featureanalysis.FeatureImportancePanel
-
- runTaskButton - Variable in class moa.gui.MultiLabelTaskManagerPanel
-
- runTaskButton - Variable in class moa.gui.MultiTargetTaskManagerPanel
-
- runTaskButton - Variable in class moa.gui.RegressionTaskManagerPanel
-
- runTaskButton - Variable in class moa.gui.TaskManagerPanel
-
- runTaskCLI(String[]) - Method in class moa.gui.experimentertab.TaskManagerTabPanel
-
- RunTasks - Class in moa.tasks
-
Task for running several experiments modifying values of parameters.
- RunTasks() - Constructor for class moa.tasks.RunTasks
-
- runVisual() - Method in class moa.gui.visualization.RunVisualizer
-
- RunVisualizer - Class in moa.gui.visualization
-
- RunVisualizer(ClusteringVisualTab, ClusteringSetupTab) - Constructor for class moa.gui.visualization.RunVisualizer
-
- SAMkNN - Class in moa.classifiers.lazy
-
Self Adjusting Memory (SAM) coupled with the k Nearest Neighbor classifier (kNN) .
- SAMkNN() - Constructor for class moa.classifiers.lazy.SAMkNN
-
- sammeOption - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- samoaAttribute(int, Attribute) - Method in class com.yahoo.labs.samoa.instances.WekaToSamoaInstanceConverter
-
Get Samoa attribute from a weka attribute.
- samoaInstance(Instance) - Method in class com.yahoo.labs.samoa.instances.WekaToSamoaInstanceConverter
-
Samoa instance from weka instance.
- samoaInstanceInformation - Variable in class com.yahoo.labs.samoa.instances.WekaToSamoaInstanceConverter
-
- samoaInstances(Instances) - Method in class com.yahoo.labs.samoa.instances.WekaToSamoaInstanceConverter
-
Samoa instances from weka instances.
- samoaInstancesInformation(Instances) - Method in class com.yahoo.labs.samoa.instances.WekaToSamoaInstanceConverter
-
Samoa instances information.
- samoaToWeka - Variable in class moa.classifiers.meta.imbalanced.CSMOTE
-
- samoaToWeka - Variable in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- SamoaToWekaInstanceConverter - Class in com.yahoo.labs.samoa.instances
-
The Class SamoaToWekaInstanceConverter.
- SamoaToWekaInstanceConverter() - Constructor for class com.yahoo.labs.samoa.instances.SamoaToWekaInstanceConverter
-
- sample() - Method in class moa.clusterers.meta.TruncatedNormal
-
- sample(Random) - Method in class moa.cluster.Cluster
-
Samples this cluster by returning a point from inside it.
- sample(Random) - Method in class moa.cluster.SphereCluster
-
Samples this cluster by returning a point from inside it.
- sampleFrequencyOption - Variable in class moa.classifiers.meta.WEKAClassifier
-
- sampleFrequencyOption - Variable in class moa.gui.experimentertab.tasks.EvaluateConceptDrift
-
- sampleFrequencyOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedChunks
-
Defines how often classifier parameters will be calculated.
- sampleFrequencyOption - Variable in class moa.gui.experimentertab.tasks.EvaluateInterleavedTestThenTrain
-
- sampleFrequencyOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePeriodicHeldOutTest
-
- sampleFrequencyOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequential
-
- sampleFrequencyOption - Variable in class moa.gui.experimentertab.tasks.EvaluatePrequentialCV
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluateConceptDrift
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluateInterleavedChunks
-
Defines how often classifier parameters will be calculated.
- sampleFrequencyOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluateModel
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluateOnlineRecommender
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluatePrequential
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialCV
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialDelayed
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialDelayedCV
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialMultiLabel
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialMultiTarget
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- sampleFrequencyOption - Variable in class moa.tasks.EvaluatePrequentialRegression
-
- sampleFrequencyOption - Variable in class moa.tasks.meta.ALPrequentialEvaluationTask
-
- SampleInfo() - Constructor for class moa.classifiers.core.driftdetection.HDDM_W_Test.SampleInfo
-
- sampleNewConfig(double, double, int) - Method in class moa.clusterers.meta.BooleanParameter
-
- sampleNewConfig(double, double, int) - Method in class moa.clusterers.meta.CategoricalParameter
-
- sampleNewConfig(double, double, int) - Method in class moa.clusterers.meta.IntegerParameter
-
- sampleNewConfig(double, double, int) - Method in interface moa.clusterers.meta.IParameter
-
- sampleNewConfig(double, double, int) - Method in class moa.clusterers.meta.NumericalParameter
-
- sampleNewConfig(double, double, int) - Method in class moa.clusterers.meta.OrdinalParameter
-
- sampleNewConfiguration(ArrayList<Double>, int) - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- sampleParent(ArrayList<Double>) - Method in class moa.clusterers.meta.EnsembleClustererAbstract
-
- samplingRate - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- samplingRate - Variable in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- samplingRate - Variable in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- samplingRateOption - Variable in class moa.classifiers.meta.imbalanced.OnlineRUSBoost
-
- samplingRateOption - Variable in class moa.classifiers.meta.imbalanced.OnlineSMOTEBagging
-
- samplingRateOption - Variable in class moa.classifiers.meta.imbalanced.OnlineUnderOverBagging
-
- saveBestEntropy - Variable in class moa.classifiers.rules.RuleClassifier
-
- saveBestEntropyNominalAttrib - Variable in class moa.classifiers.rules.RuleClassifier
-
- saveBestGlobalEntropy - Variable in class moa.classifiers.rules.RuleClassifier
-
- saveBestValGlobalEntropy - Variable in class moa.classifiers.rules.RuleClassifier
-
- saveInstancesToFile(AbstractFileSaver, Instances) - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
saves the data with the specified saver
- saveLogSelectedTasks() - Method in class moa.gui.active.ALTaskManagerPanel
-
- saveLogSelectedTasks() - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- saveLogSelectedTasks() - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- saveLogSelectedTasks() - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- saveLogSelectedTasks() - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- saveLogSelectedTasks() - Method in class moa.gui.RegressionTaskManagerPanel
-
- saveLogSelectedTasks() - Method in class moa.gui.TaskManagerPanel
-
- saveTheBest - Variable in class moa.classifiers.rules.RuleClassifier
-
- saveWorkingInstancesToFileQ() - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Queries the user for a file to save instances as, then saves the instances
in a background process.
- scalarProduct(DoubleVector, DoubleVector) - Static method in class moa.classifiers.multilabel.trees.ISOUPTree
-
- scalarProduct(DoubleVector, DoubleVector) - Method in class moa.classifiers.trees.ARFFIMTDD
-
- scalarProduct(DoubleVector, DoubleVector) - Method in class moa.classifiers.trees.FIMTDD
-
- scaleValues(double) - Method in class moa.core.DoubleVector
-
- scaleValues(float) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- scaleWeights(double) - Method in class moa.classifiers.meta.DynamicWeightedMajority
-
- scaleXResolution(boolean) - Method in class moa.gui.visualization.GraphCanvas
-
- scaleXResolution(double) - Method in class moa.gui.visualization.AbstractGraphCanvas
-
Scales the resolution on the x-axis by the given factor and updates the
canvas.
- scaleYResolution(boolean) - Method in class moa.gui.visualization.GraphCanvas
-
- scaleYResolution(double) - Method in class moa.gui.visualization.AbstractGraphCanvas
-
Scales the resolution on the y-axis by the given factor and updates the
canvas.
- scms - Variable in class moa.classifiers.meta.ADOB
-
- scms - Variable in class moa.classifiers.meta.BOLE
-
- scms - Variable in class moa.classifiers.meta.OzaBoost
-
- scms - Variable in class moa.classifiers.meta.OzaBoostAdwin
-
- score(Instance, int) - Method in class moa.classifiers.oneclass.HSTreeNode
-
If this node is a leaf node or it has a mass profile of less than sizeLimit, this returns the anomaly score for the argument instance.
- Score(double, int, boolean) - Constructor for class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator.Score
-
Constructor.
- Score(double, int, boolean) - Constructor for class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator.Score
-
Constructor.
- scores - Variable in class moa.gui.featureanalysis.FeatureImportancePanel
-
Feature importance scores produced by feature importance algorithm.
- scores - Variable in class moa.tasks.FeatureImportanceConfig
-
Scores produced by feature importance algorithm.
- scoreThreshold - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- screenshot(String, boolean, boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- screenshot(String, boolean, boolean) - Method in class moa.gui.visualization.StreamPanel
-
- ScriptingTabPanel - Class in moa.gui
-
Tab for performing scripting via jshell.
- ScriptingTabPanel() - Constructor for class moa.gui.ScriptingTabPanel
-
Initializes the tab.
- scroll - Variable in class moa.gui.experimentertab.SummaryViewer
-
- scrollPane - Variable in class moa.gui.experimentertab.TaskTextViewerPanel
-
- scrollPane - Variable in class moa.gui.TextViewerPanel
-
- SDRSplitCriterion - Class in moa.classifiers.core.splitcriteria
-
- SDRSplitCriterion() - Constructor for class moa.classifiers.core.splitcriteria.SDRSplitCriterion
-
- SDRSplitCriterionAMRules - Class in moa.classifiers.rules.core.splitcriteria
-
- SDRSplitCriterionAMRules() - Constructor for class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRules
-
- SDRSplitCriterionAMRulesNode - Class in moa.classifiers.rules.core.splitcriteria
-
- SDRSplitCriterionAMRulesNode() - Constructor for class moa.classifiers.rules.core.splitcriteria.SDRSplitCriterionAMRulesNode
-
- SEAGenerator - Class in moa.streams.generators
-
Stream generator for SEA concepts functions.
- SEAGenerator() - Constructor for class moa.streams.generators.SEAGenerator
-
- SEAGenerator.ClassFunction - Interface in moa.streams.generators
-
- searchForBestSplitOption(BinaryTreeNumericAttributeClassObserver.Node, AttributeSplitSuggestion, double[], double[], double[], boolean, SplitCriterion, double[], int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserver
-
- searchForBestSplitOption(BinaryTreeNumericAttributeClassObserverRegression.Node, AttributeSplitSuggestion, double[], double[], double[], boolean, SplitCriterion, double[], int) - Method in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
-
- searchForBestSplitOption(FIMTDDNumericAttributeClassObserver.Node, AttributeSplitSuggestion, SplitCriterion, int) - Method in class moa.classifiers.core.attributeclassobservers.FIMTDDNumericAttributeClassObserver
-
Implementation of the FindBestSplit algorithm from E.Ikonomovska et al.
- searchForBestSplitOption(MultiLabelBSTree.Node, AttributeExpansionSuggestion, MultiLabelSplitCriterion, DoubleVector[], int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTree
-
- searchForBestSplitOption(MultiLabelBSTreeFloat.Node, AttributeExpansionSuggestion, MultiLabelSplitCriterion, DoubleVector[], int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelBSTreeFloat
-
- second - Variable in class moa.clusterers.outliers.utils.mtree.utils.Pair
-
The second object.
- secondarySplitConfidenceOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- secondLine - Variable in class moa.gui.experimentertab.TaskTextViewerPanel
-
- secondLine - Variable in class moa.gui.TaskTextViewerPanel
-
- secondsToDHMSString(double) - Static method in class moa.core.StringUtils
-
- seed - Variable in class moa.classifiers.core.driftdetection.SEEDChangeDetector
-
- SEED(double, int, double, double, int) - Constructor for class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEED
-
Constructor for all required parameters.
- SEEDBlock(int) - Constructor for class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- SEEDBlock(SEEDChangeDetector.SEEDBlock) - Constructor for class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- SEEDChangeDetector - Class in moa.classifiers.core.driftdetection
-
Drift detection method as published in:
- SEEDChangeDetector() - Constructor for class moa.classifiers.core.driftdetection.SEEDChangeDetector
-
- SEEDChangeDetector.SEED - Class in moa.classifiers.core.driftdetection
-
- SEEDChangeDetector.SEEDBlock - Class in moa.classifiers.core.driftdetection
-
- SEEDChangeDetector.SEEDWindow - Class in moa.classifiers.core.driftdetection
-
- SEEDWindow(int) - Constructor for class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- SEEDWindow(int, int, int, double, double, int) - Constructor for class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- select(int, int[], int, int, int) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MedianOfWidestDimension
-
Implements computation of the kth-smallest element according
to Manber's "Introduction to Algorithms".
- SelectAllInputs - Class in moa.classifiers.rules.multilabel.inputselectors
-
Does not selects inputs
- SelectAllInputs() - Constructor for class moa.classifiers.rules.multilabel.inputselectors.SelectAllInputs
-
- SelectAllOutputs - Class in moa.classifiers.rules.multilabel.outputselectors
-
- SelectAllOutputs() - Constructor for class moa.classifiers.rules.multilabel.outputselectors.SelectAllOutputs
-
- SelectAttributesFilter - Class in moa.streams.filters
-
- SelectAttributesFilter() - Constructor for class moa.streams.filters.SelectAttributesFilter
-
- Selection - Class in moa.streams.filters
-
- Selection() - Constructor for class moa.streams.filters.Selection
-
- selectOutputsToLearn(int[]) - Method in class moa.classifiers.rules.multilabel.functions.AbstractAMRulesFunctionBasicMlLearner
-
- selectOutputsToLearn(int[]) - Method in class moa.classifiers.rules.multilabel.functions.AdaptiveMultiTargetRegressor
-
- selectOutputsToLearn(int[]) - Method in interface moa.classifiers.rules.multilabel.functions.AMRulesFunction
-
- selectOutputsToLearn(int[]) - Method in class moa.classifiers.rules.multilabel.functions.DominantLabelsClassifier
-
- selectOutputsToLearn(int[]) - Method in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- SemiSupervisedLearner - Interface in moa.classifiers
-
Learner interface for incremental semi supervised models.
- Separation - Class in moa.evaluation
-
- Separation() - Constructor for class moa.evaluation.Separation
-
- separationOption - Variable in class moa.tasks.EvaluateClustering
-
- separationOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- separatorChar - Variable in class com.github.javacliparser.ListOption
-
- seqdrift - Variable in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
-
- seqDrift1 - Variable in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
-
- SeqDrift1(double, int, double) - Constructor for class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector.SeqDrift1
-
- SeqDrift1ChangeDetector - Class in moa.classifiers.core.driftdetection
-
SeqDrift1ChangeDetector.java.
- SeqDrift1ChangeDetector() - Constructor for class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector
-
- SeqDrift1ChangeDetector.SeqDrift1 - Class in moa.classifiers.core.driftdetection
-
SeqDrift1 uses sliding window to build a sequential change detection model
that uses statistically sound guarantees defined using Bernstein Bound on
false positive and false negative rates.
- SeqDrift2(double, int) - Constructor for class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.SeqDrift2
-
SeqDrift change detector requires two parameters: significance level and
block size.
- SeqDrift2ChangeDetector - Class in moa.classifiers.core.driftdetection
-
SeqDriftChangeDetector.java.
- SeqDrift2ChangeDetector() - Constructor for class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector
-
- SeqDrift2ChangeDetector.Block - Class in moa.classifiers.core.driftdetection
-
- SeqDrift2ChangeDetector.Repository - Class in moa.classifiers.core.driftdetection
-
- SeqDrift2ChangeDetector.Reservoir - Class in moa.classifiers.core.driftdetection
-
- SeqDrift2ChangeDetector.SeqDrift2 - Class in moa.classifiers.core.driftdetection
-
SeqDrift2 uses reservoir sampling to build a sequential change detection
model that uses statistically sound guarantees defined using Bernstein Bound
on false positive and false negative rates.
- SerializeUtils - Class in com.github.javacliparser
-
Class implementing some serialize utility methods.
- SerializeUtils - Class in moa.core
-
Class implementing some serialize utility methods.
- SerializeUtils() - Constructor for class com.github.javacliparser.SerializeUtils
-
- SerializeUtils() - Constructor for class moa.core.SerializeUtils
-
- SerializeUtils.ByteCountingOutputStream - Class in com.github.javacliparser
-
- SerializeUtils.ByteCountingOutputStream - Class in moa.core
-
- serialVersionUID - Static variable in class moa.classifiers.core.attributeclassobservers.BinaryTreeNumericAttributeClassObserverRegression
-
- serialVersionUID - Static variable in class moa.classifiers.core.driftdetection.HDDM_W_Test
-
- serialVersionUID - Static variable in class moa.classifiers.rules.multilabel.errormeasurers.RelativeRootMeanSquaredErrorMT
-
- serialVersionUID - Static variable in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- set() - Method in class com.github.javacliparser.FlagOption
-
- set(int, double) - Method in class moa.recommender.rc.utils.DenseVector
-
- set(int, double) - Method in class moa.recommender.rc.utils.SparseVector
-
- set(int, double) - Method in class moa.recommender.rc.utils.Vector
-
- set(int, Instance) - Method in class com.yahoo.labs.samoa.instances.Instances
-
- set(int, T) - Method in class moa.core.AutoExpandVector
-
- set(List<Instance>, List<Instance>) - Method in class moa.classifiers.core.statisticaltests.Cramer
-
- set(List<Instance>, List<Instance>) - Method in class moa.classifiers.core.statisticaltests.KNN
-
- set(List<Instance>, List<Instance>) - Method in interface moa.classifiers.core.statisticaltests.StatisticalTest
-
This method sets the instances for later use in concurrent scenarios.
- setActionListener(ActionListener) - Method in class moa.gui.active.MeasureOverview
-
Sets the ActionListener for the radio buttons.
- setActiveXDim(int) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- setActiveXDim(int) - Method in class moa.gui.visualization.StreamPanel
-
- setActiveYDim(int) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- setActiveYDim(int) - Method in class moa.gui.visualization.StreamPanel
-
- setAcuity(double) - Method in class moa.clusterers.CobWeb
-
set the acuity.
- setAlgorithm0ValueAsCLIString(String) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- setAlgorithm0ValueAsCLIString(String) - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- setAlgorithm1ValueAsCLIString(String) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- setAlgorithm1ValueAsCLIString(String) - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- setAlgorithms(String[]) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- setAlgorithmsID(String[]) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- setAlpha(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- setAnomalyDetector(AnomalyDetector) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setAnomalyDetector(AnomalyDetector) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setArgs(String[]) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- setArrayLength(int) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- setArrayLength(int) - Method in class moa.core.DoubleVector
-
- setAttribute(int) - Method in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Sets the attribute that statistics will be displayed for.
- setAttribute(int) - Method in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Tells the panel which attribute to visualize.
- setAttributeIndex(int) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- setAttributeIndices(String) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction
-
Sets the range of attributes to use in the calculation of the distance.
- setAttributeIndices(String) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Sets the range of attributes to use in the calculation of the distance.
- setAttributeName(String) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- setAttributeNames(String[]) - Method in class moa.gui.featureanalysis.FeatureImportanceGraph
-
- setAttributes(Attribute[]) - Method in class com.yahoo.labs.samoa.instances.AttributesInformation
-
Sets the attribute information.
- setAttributes(Attribute[]) - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- setAttributes(Attribute[]) - Method in class com.yahoo.labs.samoa.instances.Instances
-
- setAttributes(Attribute[], int[]) - Method in class com.yahoo.labs.samoa.instances.AttributesInformation
-
- setAttributes(Attribute[], int[]) - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- setAttributes(Attribute[], int[]) - Method in class com.yahoo.labs.samoa.instances.Instances
-
- setAttributes(List<Attribute>, List<Integer>) - Method in class com.yahoo.labs.samoa.instances.Instances
-
- setAttributesPercentage(double) - Method in class moa.classifiers.rules.AbstractAMRules
-
- setAttributesPercentage(double) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- setAttributesPercentage(double) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- setAttributesPercentage(double) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setAttributesPercentage(double) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setAttributeValue(double) - Method in class moa.classifiers.rules.Predicates
-
- setAttributeValue(NumericAttributeBinaryRulePredicate) - Method in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- setAttributeValues(double[]) - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Sets the attribute values.
- setBestSuggestion(AttributeSplitSuggestion) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- setBlockCount(int) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- setBlockSize(int) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- setBlockSize(int) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- setBuilder(Rule.Builder) - Method in class moa.classifiers.rules.core.Rule
-
- setCenter(double[]) - Method in class moa.cluster.SphereCluster
-
- setCenter(double[]) - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Sets the representation of the ClusteringFeature
- setChangeDetector(ChangeDetector) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setChangeDetector(ChangeDetector) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setChangeListener(ChangeListener) - Method in class moa.options.ClassOptionWithListenerOption
-
- setChart(JFreeChart) - Method in class moa.gui.experimentertab.ImageChart
-
Set chart.
- setChild(int, ISOUPTree.Node) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- setChild(int, ISOUPTree.Node) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- setChild(int, ARFFIMTDD.Node) - Method in class moa.classifiers.trees.ARFFIMTDD.InnerNode
-
- setChild(int, ARFFIMTDD.Node) - Method in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- setChild(int, ARFFIMTDD.Node) - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- setChild(int, EFDT.Node) - Method in class moa.classifiers.trees.EFDT.SplitNode
-
- setChild(int, FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.InnerNode
-
- setChild(int, FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.LeafNode
-
- setChild(int, FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.Node
-
- setChild(int, HoeffdingOptionTree.Node) - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- setChild(int, HoeffdingTree.Node) - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- setChild(Iadem2.Node, int) - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- setChild(Node) - Method in class moa.clusterers.clustree.Entry
-
Setter for the child in this entry.
- setChild(AutoExpandVector<Iadem2.Node>) - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- setChildren(Iadem2.Node[]) - Method in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- setChosenIndex(int) - Method in class com.github.javacliparser.MultiChoiceOption
-
- setChosenLabel(String) - Method in class com.github.javacliparser.MultiChoiceOption
-
- setClassifier(ClassOption) - Method in class weka.classifiers.meta.MOA
-
Sets the MOA classifier to use.
- setClassIndex(int) - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- setClassIndex(int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Sets the class index.
- setClassValue(double) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Sets the class value.
- setClassValue(double) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Sets the class value.
- setClassValue(int, double) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Sets the value of an output attribute.
- setClassValue(int, double) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- setClassValueDist(DoubleVector) - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- setClock(int) - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- setClustered() - Method in class moa.clusterers.macro.dbscan.DenseMicroCluster
-
- setClusterEventsList(ArrayList<ClusterEvent>) - Method in class moa.gui.visualization.GraphCanvas
-
- setClusterIDs(Clustering) - Method in class moa.clusterers.macro.AbstractMacroClusterer
-
- setClusteringSetupTab(ClusteringSetupTab) - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- setClusterLabel(int) - Method in class moa.clusterers.dstream.GridCluster
-
- setColorCoding(Color) - Method in class moa.tasks.meta.MetaMainTask
-
Set the color coding for this task (the color which is used for multi-curve plots).
- setColoringIndex(int) - Method in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Set the coloring (class) index for the plot
- setCompressionTerm(int) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- setConfidence(double) - Static method in class moa.classifiers.trees.iadem.IademCommonProcedures
-
- setCoresetCentres(Point[]) - Method in class moa.clusterers.streamkm.CoresetCostTriple
-
- setCoresetCost(double) - Method in class moa.clusterers.streamkm.CoresetCostTriple
-
- setCurrentActivity(String, double) - Method in class moa.tasks.NullMonitor
-
- setCurrentActivity(String, double) - Method in class moa.tasks.StandardTaskMonitor
-
- setCurrentActivity(String, double) - Method in interface moa.tasks.TaskMonitor
-
Sets the description and the percentage done of the current activity.
- setCurrentActivityDescription(String) - Method in class moa.tasks.NullMonitor
-
- setCurrentActivityDescription(String) - Method in class moa.tasks.StandardTaskMonitor
-
- setCurrentActivityDescription(String) - Method in interface moa.tasks.TaskMonitor
-
Sets the description of the current activity.
- setCurrentActivityFractionComplete(double) - Method in class moa.tasks.NullMonitor
-
- setCurrentActivityFractionComplete(double) - Method in class moa.tasks.StandardTaskMonitor
-
- setCurrentActivityFractionComplete(double) - Method in interface moa.tasks.TaskMonitor
-
Sets the percentage done of the current activity
- setCurrentObject(Object) - Method in class com.github.javacliparser.AbstractClassOption
-
Sets current object.
- setCurrentObject(Object) - Method in class moa.options.AbstractClassOption
-
Sets current object.
- setCutoff(double) - Method in class moa.clusterers.CobWeb
-
set the cutoff
- setData(List<String>, List<double[]>) - Method in class moa.evaluation.preview.LearningCurve
-
- setDataset(Instances) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Sets the dataset.
- setDataset(Instances) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Sets the dataset.
- setDensityTimeStamp(int) - Method in class moa.clusterers.dstream.CharacteristicVector
-
- setDerived(int) - Method in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Sets the gui elements for fields that are stored in the AttributeStats
structure.
- setDimensionComobBoxes(int) - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- setDimensionComobBoxes(int) - Method in class moa.gui.outliertab.OutlierVisualTab
-
- setDirection(double[]) - Method in class moa.gui.visualization.ClusterPanel
-
- setDirection(double[]) - Method in class moa.gui.visualization.OutlierPanel
-
- setDistanceFunction(DistanceFunction) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
sets the distance function to use for nearest neighbour search.
- setDistanceFunction(DistanceFunction) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
sets the distance function to use for nearest neighbour search.
- setDoNotNormalizeFeatureScore(boolean) - Method in class moa.tasks.FeatureImportanceConfig
-
- setDontNormalize(boolean) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Sets whether if the attribute values are to be normalized in distance
calculation.
- setEditState(String) - Method in class com.github.javacliparser.gui.ClassOptionEditComponent
-
- setEditState(String) - Method in class com.github.javacliparser.gui.ClassOptionWithNamesEditComponent
-
- setEditState(String) - Method in class com.github.javacliparser.gui.FileOptionEditComponent
-
- setEditState(String) - Method in class com.github.javacliparser.gui.FlagOptionEditComponent
-
- setEditState(String) - Method in class com.github.javacliparser.gui.FloatOptionEditComponent
-
- setEditState(String) - Method in class com.github.javacliparser.gui.IntOptionEditComponent
-
- setEditState(String) - Method in class com.github.javacliparser.gui.MultiChoiceOptionEditComponent
-
- setEditState(String) - Method in interface com.github.javacliparser.gui.OptionEditComponent
-
Sets the state of the component
- setEditState(String) - Method in class com.github.javacliparser.gui.StringOptionEditComponent
-
- setEditState(String) - Method in class moa.gui.WEKAClassOptionEditComponent
-
- setEnabled(int, boolean) - Method in class moa.evaluation.MeasureCollection
-
- setEpsilon(double) - Method in class moa.classifiers.functions.AdaGrad
-
Set the epsilon value.
- setEpsilonPrime(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- setError(double) - Method in class moa.classifiers.rules.core.voting.Vote
-
- setError(double) - Method in class moa.classifiers.rules.multilabel.core.voting.MultiLabelVote
-
- setErrorMeasurer(MultiLabelErrorMeasurer) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setErrorMeasurer(MultiLabelErrorMeasurer) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setErrorText(FailedTaskReport) - Method in class moa.gui.active.ALTaskTextViewerPanel
-
Displays the error message.
- setEstimador(AbstractChangeDetector) - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- setEuclideanDistanceFunction(EuclideanDistance) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Sets the EuclideanDistance object to use for
splitting nodes.
- setEvents - Variable in class moa.clusterers.outliers.MCOD.MCODBase.EventQueue
-
- setEvents - Variable in class moa.clusterers.outliers.SimpleCOD.SimpleCODBase.EventQueue
-
- setEventsList(ArrayList<ClusterEvent>) - Method in class moa.gui.experimentertab.tasks.ConceptDriftMainTask
-
- setEventsList(ArrayList<ClusterEvent>) - Method in class moa.tasks.AuxiliarMainTask
-
- setEventsList(ArrayList<ClusterEvent>) - Method in class moa.tasks.ClassificationMainTask
-
- setEventsList(ArrayList<ClusterEvent>) - Method in class moa.tasks.ConceptDriftMainTask
-
- setEventsList(ArrayList<ClusterEvent>) - Method in class moa.tasks.MultiLabelMainTask
-
- setEventsList(ArrayList<ClusterEvent>) - Method in class moa.tasks.MultiTargetMainTask
-
- setEventsList(ArrayList<ClusterEvent>) - Method in class moa.tasks.RegressionMainTask
-
- setFeatureImportance(double[][]) - Method in class moa.gui.featureanalysis.FeatureImportanceGraph
-
- setFeatureImportanceScores(double[][]) - Method in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
set table data model include: instances + feature importance scores
- setFeatureRange(String) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
Parse String to number.
- setFeatureRangeEndIndex(int) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- setFeatureRangeStartIndex(int) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- setFileName(String) - Method in class moa.gui.experimentertab.Measure
-
- setFirst(T) - Method in class moa.recommender.rc.utils.Pair
-
- setGenerator(ClassOption) - Method in class weka.datagenerators.classifiers.classification.MOA
-
Sets the MOA stream generator to use.
- setGraph(String) - Method in class moa.gui.experimentertab.TaskTextViewerPanel
-
- setGraph(String) - Method in class moa.gui.TaskTextViewerPanel
-
- setGraph(MeasureCollection[], MeasureCollection[], double[], Color[]) - Method in class moa.gui.visualization.GraphScatter
-
Draws a scatter graph based on the varied parameter and the measures.
- setGraph(MeasureCollection[], MeasureCollection[], double[], Color[]) - Method in class moa.gui.visualization.ParamGraphCanvas
-
Sets the scatter graph.
- setGraph(MeasureCollection[], MeasureCollection[], int[], int, Color[]) - Method in class moa.gui.visualization.ProcessGraphCanvas
-
Sets the graph containing multiple curves.
- setGraph(MeasureCollection[], MeasureCollection[], int[], Color[]) - Method in class moa.gui.visualization.GraphMultiCurve
-
Updates the measure collection information and repaints the curves.
- setGraph(MeasureCollection[], MeasureCollection[], Color[]) - Method in class moa.gui.visualization.AbstractGraphPlot
-
Sets the graph by updating the measures and currently measure index.
- setGraph(MeasureCollection, MeasureCollection, int) - Method in class moa.gui.visualization.GraphCurve
-
- setGraph(MeasureCollection, MeasureCollection, int, int) - Method in class moa.gui.visualization.GraphCanvas
-
- setGraph(Preview, Color[]) - Method in class moa.gui.active.ALTaskTextViewerPanel
-
Updates the graph based on the information given by the preview.
- setGridDensity(double, int) - Method in class moa.clusterers.dstream.CharacteristicVector
-
- setGroundTruth(double) - Method in class moa.cluster.Cluster
-
- setGroundTruthLayerVisibility(boolean) - Method in class moa.gui.visualization.StreamPanel
-
- setGroundTruthVisibility(boolean) - Method in class moa.gui.visualization.RunVisualizer
-
- setHead(SEEDChangeDetector.SEEDBlock) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- setHeader(int) - Method in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Sets the labels for fields we can determine just from the instance header.
- setHeight(int) - Method in class moa.gui.experimentertab.ImageChart
-
Set chart height.
- setHighlightedClusterPanel(ClusterPanel) - Method in class moa.gui.visualization.StreamPanel
-
- setHighlightedOutlierPanel(OutlierPanel) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- setId(double) - Method in class moa.cluster.Cluster
-
- setId(int) - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
-
- setIndex(int) - Method in class moa.gui.experimentertab.Measure
-
Sets the index of measure
- setIndexValues(int[]) - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Sets the index values.
- setIndicesRelevants(int[]) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Sets the indices of relevant features.
- setInfogainSum(HashMap<Integer, Double>) - Method in class moa.classifiers.trees.EFDT.Node
-
- setInput(double) - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- setInput(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEED
-
Main method for passing in input values and performing drift detection
- setInput(double) - Method in class moa.classifiers.core.driftdetection.SeqDrift1ChangeDetector.SeqDrift1
-
- setInput(double) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.SeqDrift2
-
This method can be used to directly interface with SeqDrift change
detector.
- setInput(double, double) - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- setInputAttributesSelector(InputAttributesSelector) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setInputAttributesSelector(InputAttributesSelector) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setInputStream(ExampleStream) - Method in class moa.streams.filters.AbstractStreamFilter
-
- setInputStream(ExampleStream) - Method in interface moa.streams.filters.StreamFilter
-
Sets the input stream to the filter
- setInputStream(ExampleStream<Example<Instance>>) - Method in class moa.streams.filters.AbstractMultiLabelStreamFilter
-
- setInputStream(ExampleStream<Example<Instance>>) - Method in interface moa.streams.filters.MultiLabelStreamFilter
-
Sets the input stream to the filter
- setInstanceInformation(InstanceInformation) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setInstanceList(int[]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Sets the master index array containing indices of the
training instances.
- setInstances(Instances) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction
-
Sets the instances.
- setInstances(Instances) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Builds the KDTree on the given set of instances.
- setInstances(Instances) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Sets the training instances on which the tree is (or is
to be) built.
- setInstances(Instances) - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch
-
Sets the instances comprising the current neighbourhood.
- setInstances(Instances) - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch
-
Sets the instances.
- setInstances(Instances) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Sets the instances.
- setInstances(Instances) - Method in class moa.gui.featureanalysis.AttributeSelectionPanel
-
Sets the instances who's attribute names will be displayed.
- setInstances(Instances) - Method in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Tells the panel to use a new set of instances.
- setInstances(Instances) - Method in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
Sets the instances who's attribute names will be displayed.
- setInstances(Instances) - Method in class moa.gui.featureanalysis.FeatureImportancePanel
-
Tells the panel to use a new base set of instances.
- setInstances(Instances) - Method in class moa.gui.featureanalysis.InstancesSummaryPanel
-
Tells the panel to use a new set of instances.
- setInstances(Instances) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
Set dataset which is the data source of line graph or scatter diagram.
- setInstances(Instances) - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Tells the panel to use a new base set of instances.
- setInstances(Instances) - Method in class moa.tasks.FeatureImportanceConfig
-
- setInstances(Instances) - Method in class moa.gui.featureanalysis.AttributeVisualizationPanel
-
Sets the instances for use
- setInstancesFromFile2(String) - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
- setInstancesFromFileQ() - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Queries the user for a file to load instances from, then loads the
instances in a background process.
- setInstancesSeen(int) - Method in class moa.classifiers.rules.functions.Perceptron
-
- setInstanceTransformer(InstanceTransformer) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setInstanceTransformer(InstanceTransformer) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setInstSeenSinceLastSplitAttempt(double) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- setIntEndIndex(int) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- setIntStartIndex(int) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- setInvertSelection(boolean) - Method in interface moa.classifiers.lazy.neighboursearch.DistanceFunction
-
Sets whether the matching sense of attribute indices is inverted or not.
- setInvertSelection(boolean) - Method in class moa.classifiers.lazy.neighboursearch.NormalizableDistance
-
Sets whether the matching sense of attribute indices is inverted or not.
- setIsLastSubtaskOnLevel(boolean[], boolean) - Method in class moa.tasks.meta.MetaMainTask
-
Set the list of booleans indicating if the current branch in the
subtask tree is the last one on its respective level.
- setItemCount(int) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- setLabel(int) - Method in class moa.clusterers.dstream.CharacteristicVector
-
- setLambda(double) - Method in class moa.classifiers.functions.SGD
-
Set the value of lambda to use
- setLambda(double) - Method in class moa.classifiers.functions.SGDMultiClass
-
Set the value of lambda to use
- setLambda(double) - Method in class moa.classifiers.functions.SPegasos
-
Set the value of lambda to use
- setLatestPreview(Object) - Method in class moa.gui.experimentertab.ExpPreviewPanel
-
- setLatestResultPreview(Object) - Method in class moa.tasks.NullMonitor
-
- setLatestResultPreview(Object) - Method in class moa.tasks.StandardTaskMonitor
-
- setLatestResultPreview(Object) - Method in interface moa.tasks.TaskMonitor
-
Sets the current result to preview
- setLearner(MultiLabelLearner) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setLearner(MultiLabelLearner) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setLearningNode(RuleActiveLearningNode) - Method in class moa.classifiers.rules.core.Rule
-
- setLearningRate(double) - Method in class moa.classifiers.functions.SGD
-
Set the learning rate.
- setLearningRate(double) - Method in class moa.classifiers.functions.SGDMultiClass
-
Set the learning rate.
- setLearningRatio(double) - Method in class moa.classifiers.rules.functions.Perceptron
-
- setList(Option[]) - Method in class com.github.javacliparser.ListOption
-
- setlistAttributes(int[]) - Method in class moa.classifiers.trees.LimAttHoeffdingTree.LimAttLearningNode
-
- setlistAttributes(int[]) - Method in class moa.classifiers.trees.LimAttHoeffdingTree
-
- setLog(Logger) - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
Sets the Logger to receive informational messages
- setLossFunction(int) - Method in class moa.classifiers.functions.SGD
-
Set the loss function to use.
- setLossFunction(int) - Method in class moa.classifiers.functions.SGDMultiClass
-
Set the loss function to use.
- setLossFunction(int) - Method in class moa.classifiers.functions.SPegasos
-
Set the loss function to use.
- setLowerXValue(double) - Method in class moa.gui.visualization.AbstractGraphAxes
-
Sets the lower value for the x-axis.
- setLowerXValue(double) - Method in class moa.gui.visualization.AbstractGraphPlot
-
Sets the lower value for the x-axis.
- setLRate(double) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- setMacroLayerVisibility(boolean) - Method in class moa.gui.visualization.StreamPanel
-
- setMacroVisibility(boolean) - Method in class moa.gui.visualization.RunVisualizer
-
- setMaxBins(int) - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- setMaxBins(int) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- setMaxBins(int) - Method in interface moa.classifiers.trees.iadem.IademNumericAttributeObserver
-
- setMaxBins(int) - Method in class moa.classifiers.trees.iadem.IademVFMLNumericAttributeClassObserver
-
- setMaxInstInLeaf(int) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Sets the maximum number of instances in a leaf.
- setMaxSize(int) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Reservoir
-
- setMaxSize(int) - Method in class moa.classifiers.trees.ASHoeffdingTree
-
- setMaxXValue(double) - Method in class moa.gui.visualization.AbstractGraphAxes
-
Sets the maximum x value
- setMaxXValue(double) - Method in class moa.gui.visualization.AbstractGraphPlot
-
Sets maximum x value.
- setMaxXValue(int) - Method in class moa.gui.visualization.GraphAxes
-
- setMaxYValue(double) - Method in class moa.gui.visualization.AbstractGraphAxes
-
Sets the maximum y value
- setMaxYValue(double) - Method in class moa.gui.visualization.AbstractGraphPlot
-
Sets maximum y value.
- setMC - Variable in class moa.clusterers.outliers.MCOD.MCODBase
-
- setMeasurePerformance(boolean) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Sets whether to calculate the performance statistics or not.
- setMeasures(boolean[]) - Method in class moa.tasks.EvaluateClustering
-
- setMeasures(MeasureCollection[], ActionListener) - Method in class moa.gui.outliertab.OutlierVisualEvalPanel
-
- setMeasures(MeasureCollection[], MeasureCollection[], ActionListener) - Method in class moa.gui.clustertab.ClusteringVisualEvalPanel
-
- setMeasureSelected(int) - Method in class moa.gui.visualization.AbstractGraphCanvas
-
Sets the currently selected measure index.
- setMeasureSelected(int) - Method in class moa.gui.visualization.AbstractGraphPlot
-
Sets the currently selected measure index.
- setMeasureValue(String, double) - Method in class moa.cluster.Cluster
-
- setMeasureValue(String, double) - Method in class moa.gui.visualization.DataPoint
-
- setMeasureValue(String, String) - Method in class moa.cluster.Cluster
-
- setMeasureValue(String, String) - Method in class moa.gui.visualization.DataPoint
-
- SetMessagePrinter(MyBaseOutlierDetector.PrintMsg) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- setMicroLayerVisibility(boolean) - Method in class moa.gui.visualization.RunVisualizer
-
- setMicroLayerVisibility(boolean) - Method in class moa.gui.visualization.StreamPanel
-
- setMinBoxRelWidth(double) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Sets the minimum relative box width.
- setMinXValue(double) - Method in class moa.gui.visualization.AbstractGraphAxes
-
Sets the minimum x value
- setMinXValue(double) - Method in class moa.gui.visualization.AbstractGraphPlot
-
Sets minimum x value.
- setMissing(int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Sets an attribute as missing
- setMissing(int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- setMissing(Attribute) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Sets an attribute as missing
- setMissing(Attribute) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- setModelContext(InstancesHeader) - Method in class moa.classifiers.AbstractClassifier
-
- setModelContext(InstancesHeader) - Method in class moa.classifiers.active.ALRandom
-
- setModelContext(InstancesHeader) - Method in class moa.classifiers.active.ALUncertainty
-
- setModelContext(InstancesHeader) - Method in class moa.classifiers.lazy.kNN
-
- setModelContext(InstancesHeader) - Method in class moa.classifiers.lazy.SAMkNN
-
- setModelContext(InstancesHeader) - Method in class moa.classifiers.meta.HeterogeneousEnsembleAbstract
-
- setModelContext(InstancesHeader) - Method in class moa.clusterers.AbstractClusterer
-
- setModelContext(InstancesHeader) - Method in interface moa.clusterers.Clusterer
-
- setModelContext(InstancesHeader) - Method in interface moa.learners.Learner
-
Sets the reference to the header of the data stream.
- setN(double) - Method in class moa.cluster.CFCluster
-
- setName(String) - Method in class moa.gui.experimentertab.ImageChart
-
Set the image name.
- setName(String) - Method in class moa.gui.experimentertab.Measure
-
Sets the name of measure
- setName(String) - Method in class moa.gui.experimentertab.Stream
-
Sets the name of stream
- setNameSuffix(String) - Method in class moa.tasks.meta.MetaMainTask
-
Set a suffix for the tasks display name.
- setNaNSubstitute(double) - Method in class moa.tasks.FeatureImportanceConfig
-
- setNewTree() - Method in class moa.classifiers.trees.iadem.Iadem3Subtree
-
- setNext(SEEDChangeDetector.SEEDBlock) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- setNIterations(int) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- setNode(Node) - Method in class moa.clusterers.clustree.Entry
-
- setNodeList(List<RuleSplitNode>) - Method in class moa.classifiers.rules.core.Rule
-
- setNodeSplitter(KDTreeNodeSplitter) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Sets the splitting method to use to split the nodes of the KDTree.
- setNodeWidthNormalization(boolean) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Sets whether if a nodes region is normalized
or not.
- setNominalObserverOption(NominalStatisticsObserver) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setNominalObserverOption(NominalStatisticsObserver) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setNormalizeNodeWidth(boolean) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Sets the flag for normalizing the widths of a KDTree Node by the width of
the dimension in the universe.
- setNumberAttributes(int) - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Sets the number of attributes.
- setNumberOfLeaves(int) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- setNumberOfNodes(int) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- setNumericObserverOption(NumericStatisticsObserver) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setNumericObserverOption(NumericStatisticsObserver) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setNumLabels(int) - Method in class moa.core.MultilabelInstance
-
- setNumPoints(int) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Sets the number of points of the ClusteringFeature.
- setObserver(ObserverMOAObject) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- setObserver(ObserverMOAObject) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- setOptions(String[]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Parses a given list of options.
- setOptions(String[]) - Method in class weka.classifiers.meta.MOA
-
Parses a given list of options.
- setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.MOA
-
Parses a list of options for this object.
- setOptions(String[], String[], int) - Method in class moa.options.EditableMultiChoiceOption
-
Set new options for this MultiChoiceOption and refresh the edit
component.
- setOutiler(boolean) - Method in class moa.clusterers.outliers.AnyOut.util.DataObject
-
- setOutlierDetector(MyBaseOutlierDetector) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- setOutlierSetupTab(OutlierSetupTab) - Method in class moa.gui.outliertab.OutlierVisualTab
-
- setOutliersVisibility(boolean) - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- setOutliersVisibility(boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- setOutputAttributesSelector(OutputAttributesSelector) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setOutputAttributesSelector(OutputAttributesSelector) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setOutputsToLearn(int[]) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setOwner(Rule) - Method in class moa.classifiers.rules.core.Rule.Builder
-
- setPanelTitle(String) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- setPanelTitle(String) - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- setParameters(String) - Method in class moa.gui.featureanalysis.FeatureImportancePanel
-
Parse parameter windowSize from user's configuration or preference。
The parameter windowSize is used to check whether the total instance number is bigger
than windowSize after user click the Run button and before the feature importance task
being executed.
- setParent(ISOUPTree.SplitNode) - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
Set the parent node
- setParent(ARFFIMTDD.Node) - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
Set the parent node
- setParent(EFDT.EFDTSplitNode) - Method in class moa.classifiers.trees.EFDT.EFDTLearningNode
-
- setParent(EFDT.EFDTSplitNode) - Method in interface moa.classifiers.trees.EFDT.EFDTNode
-
- setParent(EFDT.EFDTSplitNode) - Method in class moa.classifiers.trees.EFDT.EFDTSplitNode
-
- setParent(FIMTDD.Node) - Method in class moa.classifiers.trees.FIMTDD.Node
-
Set the parent node
- setParent(Iadem2.Node) - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- setParentEntry(Entry) - Method in class moa.clusterers.clustree.Entry
-
- setPartitionIdx(int) - Method in class moa.tasks.meta.ALMultiParamTask
-
- setPath(String) - Method in class moa.gui.experimentertab.ReadFile
-
Sets the directory of the results file.
- setPauseInterval(int) - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- setPauseInterval(int) - Method in class moa.gui.outliertab.OutlierVisualTab
-
- setPerceptron(Perceptron) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- setPointLayerVisibility(boolean) - Method in class moa.gui.visualization.RunVisualizer
-
- setPointsVisibility(boolean) - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- setPointsVisibility(boolean) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- setPointVisibility(boolean) - Method in class moa.gui.visualization.StreamPanel
-
- setPredicate(Predicate) - Method in class moa.classifiers.rules.multilabel.core.AttributeExpansionSuggestion
-
- setPreferredScrollableViewportSize(Dimension) - Method in class moa.gui.featureanalysis.AttributeSelectionPanel
-
- setPreferredScrollableViewportSize(Dimension) - Method in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
- setPreferredSize() - Method in class moa.gui.visualization.AbstractGraphCanvas
-
Sets the preferred canvas size.
- setPreferredSize() - Method in class moa.gui.visualization.ParamGraphCanvas
-
- setPreferredSize() - Method in class moa.gui.visualization.ProcessGraphCanvas
-
- setPreview(int, CollectionElementType) - Method in class moa.evaluation.preview.PreviewCollection
-
- setPreview(Preview) - Method in class moa.gui.PreviewTableModel
-
- setPreviewPanel(ALPreviewPanel) - Method in class moa.gui.active.ALTaskManagerPanel
-
- setPreviewPanel(PreviewPanel) - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- setPreviewPanel(PreviewPanel) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- setPreviewPanel(PreviewPanel) - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- setPreviewPanel(PreviewPanel) - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- setPreviewPanel(PreviewPanel) - Method in class moa.gui.RegressionTaskManagerPanel
-
- setPreviewPanel(PreviewPanel) - Method in class moa.gui.TaskManagerPanel
-
- setPrevious(SEEDChangeDetector.SEEDBlock) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- setProcessedPointsCounter(int) - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- setProcessedPointsCounter(int) - Method in class moa.gui.outliertab.OutlierVisualTab
-
- setProcessFrequency(int) - Method in class moa.gui.visualization.GraphAxes
-
- setProcessFrequency(int) - Method in class moa.gui.visualization.GraphMultiCurve
-
Sets the minimum process frequency, which may be used to stretch or
compress curves.
- setProcessFrequency(int) - Method in class moa.gui.visualization.ProcessGraphAxes
-
Sets the process frequency
- SetProgressInterval(int) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- setRadii(double[]) - Method in class moa.clusterers.streamkm.CoresetCostTriple
-
- setRadius(double) - Method in class moa.cluster.SphereCluster
-
- setRandomGenerator(Random) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setRandomGenerator(Random) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setRandomSeed(int) - Method in class moa.classifiers.AbstractClassifier
-
- setRandomSeed(int) - Method in class moa.classifiers.rules.AbstractAMRules
-
- setRandomSeed(int) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- setRandomSeed(int) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- setRandomSeed(int) - Method in class moa.clusterers.AbstractClusterer
-
- setRandomSeed(int) - Method in interface moa.clusterers.Clusterer
-
- setRandomSeed(int) - Method in interface moa.learners.Learner
-
Sets the seed for random number generation.
- setRange(int[]) - Method in class com.github.javacliparser.RangeOption
-
- setRange(String) - Method in class com.yahoo.labs.samoa.instances.Range
-
Sets the range from a string representation.
- setRangeOutputIndices(Range) - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- setRangeOutputIndices(Range) - Method in class com.yahoo.labs.samoa.instances.Instances
-
- setRating(int, int, double) - Method in class moa.recommender.rc.data.AbstractRecommenderData
-
- setRating(int, int, double) - Method in class moa.recommender.rc.data.impl.MemRecommenderData
-
- setRating(int, int, double) - Method in interface moa.recommender.rc.data.RecommenderData
-
- setRelationName(String) - Method in class com.yahoo.labs.samoa.instances.InstanceInformation
-
- setRelationName(String) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Sets the relation name.
- setRemoveTime(int) - Method in class moa.clusterers.dstream.CharacteristicVector
-
- setRequiredCapabilities(CapabilityRequirement) - Static method in class moa.gui.ClassOptionSelectionPanel
-
Sets the capability requirement of listed classes.
- setResetTree() - Method in class moa.classifiers.trees.ASHoeffdingTree
-
- setResultsFolder(String) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- setRFactor(double) - Method in class moa.recommender.rc.predictor.impl.BRISMFPredictor
-
- setRoot(boolean) - Method in class moa.classifiers.trees.EFDT.EFDTLearningNode
-
- setRoot(boolean) - Method in interface moa.classifiers.trees.EFDT.EFDTNode
-
- setRoot(boolean) - Method in class moa.classifiers.trees.EFDT.EFDTSplitNode
-
- setRuleNumberID(int) - Method in class moa.classifiers.rules.core.Rule
-
- setRuleNumberID(int) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setRuleOptions(MultiLabelRule) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- setRuleOptions(MultiLabelRule) - Method in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- setSaveExperimentsPath(String) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- setSaveInstanceData(boolean) - Method in class moa.clusterers.CobWeb
-
Set the value of saveInstances.
- setSecond(U) - Method in class moa.recommender.rc.utils.Pair
-
- setSeed(byte[]) - Method in class moa.clusterers.streamkm.MTRandom
-
This method resets the state of this instance using the byte
array of seed data provided.
- setSeed(int[]) - Method in class moa.clusterers.streamkm.MTRandom
-
This method resets the state of this instance using the integer
array of seed data provided.
- setSeed(long) - Method in class moa.clusterers.streamkm.MTRandom
-
This method resets the state of this instance using the 64
bits of seed data provided.
- setSelectedAttributeIndices(int[]) - Method in class moa.gui.featureanalysis.FeatureImportanceGraph
-
- setSelectedAttributes(boolean[]) - Method in class moa.gui.featureanalysis.AttributeSelectionPanel
-
Set the selected attributes in the widget.
- setSelectedAttributes(boolean[]) - Method in class moa.gui.featureanalysis.FeatureImportanceDataModelPanel
-
Set the selected attributes in the widget.
- setSelectedPlotInfo(int, String, int, String) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
User set plot related parameters in GUI such as plot type, selected attribute
- setSelectedPlotItem(String) - Method in class moa.gui.featureanalysis.LineAndScatterPanel
-
- SetShowProgress(boolean) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- setShowZeroInstancesAsUnknown(boolean) - Method in class moa.gui.featureanalysis.InstancesSummaryPanel
-
Set whether to show zero instances as unknown (i.e.
- setSize() - Method in class moa.gui.visualization.AbstractGraphCanvas
-
Sets the canvas size.
- setSize() - Method in class moa.gui.visualization.ParamGraphCanvas
-
- setSize() - Method in class moa.gui.visualization.ProcessGraphCanvas
-
- setSkipIdentical(boolean) - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch
-
Sets the property to skip identical instances (with distance zero from
the target) from the set of neighbours returned.
- setSourceClustering(Clustering) - Method in class moa.clusterers.ClusterGenerator
-
- setSpecialization(boolean) - Method in class moa.classifiers.rules.featureranking.messages.RuleExpandedMessage
-
- setSpeed(int) - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- setSpeed(int) - Method in class moa.gui.visualization.RunVisualizer
-
- setSplit(boolean) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- setSplitCriterion(MultiLabelSplitCriterion) - Method in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- setSplitCriterion(MultiLabelSplitCriterion) - Method in class moa.classifiers.rules.multilabel.core.MultiLabelRule
-
- setSplitIndex(int) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- setSplitMeasure(String) - Method in class moa.classifiers.trees.iadem.IademSplitCriterion
-
- setSporadic(boolean) - Method in class moa.clusterers.dstream.CharacteristicVector
-
- setStandardDeviationPainted(boolean) - Method in class moa.gui.visualization.AbstractGraphCanvas
-
Sets the value of the plotPlanel for isStandardDeviationPainted.
- setStandardDeviationPainted(boolean) - Method in class moa.gui.visualization.AbstractGraphPlot
-
Sets the value for isStandardDeviationPainted.
- setStatisticsBranchSplit(double[]) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- setStatisticsNewRuleActiveLearningNode(double[]) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- setStatisticsOtherBranchSplit(double[]) - Method in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- setStd(Double) - Method in class moa.gui.experimentertab.Measure
-
Sets the standard deviation
- setStreamIndex(int, String) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- setStreams(String[]) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- setStreamsID(String[]) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- setStreamValueAsCLIString(String) - Method in class moa.gui.clustertab.ClusteringAlgoPanel
-
- setStreamValueAsCLIString(String) - Method in class moa.gui.outliertab.OutlierAlgoPanel
-
- setSumPoints(double[]) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Sets the sum of points of the ClusteringFeature.
- setSumSquaredLength(double) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Sets the sum of the squared lengths of the ClusteringFeature.
- setSymbol(double) - Method in class moa.classifiers.rules.Predicates
-
- setTable(AttributeStats, int) - Method in class moa.gui.featureanalysis.AttributeSummaryPanel
-
Creates a tablemodel for the attribute being displayed
- setTail(SEEDChangeDetector.SEEDBlock) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- setTargetMean(TargetMean) - Method in class moa.classifiers.rules.core.RuleActiveRegressionNode
-
- setTask(String) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- setTaskString(String) - Method in class moa.gui.active.ALTaskManagerPanel
-
- setTaskString(String) - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- setTaskString(String) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- setTaskString(String) - Method in class moa.gui.featureanalysis.FeatureImportancePanel
-
- setTaskString(String) - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- setTaskString(String) - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- setTaskString(String) - Method in class moa.gui.RegressionTaskManagerPanel
-
- setTaskString(String) - Method in class moa.gui.TaskManagerPanel
-
- setTaskString(String, boolean) - Method in class moa.gui.active.ALTaskManagerPanel
-
- setTaskString(String, boolean) - Method in class moa.gui.AuxiliarTaskManagerPanel
-
- setTaskString(String, boolean) - Method in class moa.gui.conceptdrift.CDTaskManagerPanel
-
- setTaskString(String, boolean) - Method in class moa.gui.featureanalysis.FeatureImportancePanel
-
- setTaskString(String, boolean) - Method in class moa.gui.MultiLabelTaskManagerPanel
-
- setTaskString(String, boolean) - Method in class moa.gui.MultiTargetTaskManagerPanel
-
- setTaskString(String, boolean) - Method in class moa.gui.RegressionTaskManagerPanel
-
- setTaskString(String, boolean) - Method in class moa.gui.TaskManagerPanel
-
- setTaskThreadToPreview(ExpTaskThread) - Method in class moa.gui.experimentertab.ExpPreviewPanel
-
- setTaskThreadToPreview(ALTaskThread) - Method in class moa.gui.active.ALPreviewPanel
-
Sets the TaskThread that will be previewed.
- setTaskThreadToPreview(TaskThread) - Method in class moa.gui.PreviewPanel
-
- setTested(boolean) - Method in class moa.classifiers.core.driftdetection.SeqDrift2ChangeDetector.Block
-
- setText(Object) - Method in class moa.gui.TaskTextViewerPanel
-
- setText(String) - Method in class moa.gui.experimentertab.TaskTextViewerPanel
-
- setText(String) - Method in class moa.gui.TextViewerPanel
-
- setText(Preview) - Method in class moa.gui.active.ALTaskTextViewerPanel
-
Updates the preview table based on the information given by preview.
- setText(Preview) - Method in class moa.gui.TaskTextViewerPanel
-
Updates the preview table based on the information given by preview.
- setText(FailedTaskReport) - Method in class moa.gui.TaskTextViewerPanel
-
Displays the error message.
- setThreads(int) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- setThreshold(double) - Method in class moa.clusterers.kmeanspm.ClusteringFeature
-
Sets the threshold of the ClusteringFeature.
- setThreshold(double) - Method in class moa.clusterers.kmeanspm.ClusteringTreeNode
-
Gets the threshold of this node.
- setTimestamp(long) - Method in class moa.clusterers.denstream.Timestamp
-
- setTotal(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- setTotal(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- SetTrace(boolean) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- setTree(Iadem2) - Method in class moa.classifiers.trees.iadem.Iadem2.Node
-
- setTreeRoot(Iadem2.Node) - Method in class moa.classifiers.trees.iadem.Iadem2
-
- setType(boolean) - Method in class moa.gui.experimentertab.Measure
-
Sets the type of measure
- setUpdateTime(int) - Method in class moa.clusterers.dstream.CharacteristicVector
-
- setUpper(int) - Method in class com.yahoo.labs.samoa.instances.Range
-
- setUpperXValue(double) - Method in class moa.gui.visualization.AbstractGraphAxes
-
Sets the upper value for the x-axis.
- setUpperXValue(double) - Method in class moa.gui.visualization.AbstractGraphPlot
-
Sets the upper value for the x-axis.
- setUpperYValue(double) - Method in class moa.gui.visualization.AbstractGraphAxes
-
Sets the upper value for the y-axis.
- setUpperYValue(double) - Method in class moa.gui.visualization.AbstractGraphPlot
-
Sets the upper value for the y-axis.
- SetUserInfo(boolean, boolean, MyBaseOutlierDetector.PrintMsg, int) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- setValue(boolean) - Method in class com.github.javacliparser.FlagOption
-
- setValue(double) - Method in class com.github.javacliparser.FloatOption
-
- setValue(double) - Method in class moa.classifiers.rules.Predicates
-
- setValue(int) - Method in class com.github.javacliparser.IntOption
-
- setValue(int) - Method in class moa.clusterers.meta.IntegerParameter
-
- setValue(int, double) - Method in class com.yahoo.labs.samoa.instances.DenseInstanceData
-
Sets the value.
- setValue(int, double) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Sets the value of an attribute.
- setValue(int, double) - Method in interface com.yahoo.labs.samoa.instances.InstanceData
-
Sets the value.
- setValue(int, double) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Sets the value.
- setValue(int, double) - Method in class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Sets the value.
- setValue(int, double) - Method in class moa.core.DoubleVector
-
- setValue(int, float) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- setValue(Attribute, double) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Sets the value of an attribute.
- setValue(Attribute, double) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
- setValue(Instance, int, double, boolean) - Method in class com.yahoo.labs.samoa.instances.ArffLoader
-
- setValue(Double) - Method in class moa.gui.experimentertab.Measure
-
Sets the value of measure
- setValue(String) - Method in class com.github.javacliparser.StringOption
-
- setValues(DoubleVector) - Method in class moa.gui.experimentertab.Measure
-
- setValueViaCLIString(String) - Method in class com.github.javacliparser.AbstractClassOption
-
- setValueViaCLIString(String) - Method in class com.github.javacliparser.ClassOption
-
- setValueViaCLIString(String) - Method in class com.github.javacliparser.FlagOption
-
- setValueViaCLIString(String) - Method in class com.github.javacliparser.FloatOption
-
- setValueViaCLIString(String) - Method in class com.github.javacliparser.IntOption
-
- setValueViaCLIString(String) - Method in class com.github.javacliparser.ListOption
-
- setValueViaCLIString(String) - Method in class com.github.javacliparser.MultiChoiceOption
-
- setValueViaCLIString(String) - Method in interface com.github.javacliparser.Option
-
Sets value of this option via the Command Line Interface text
- setValueViaCLIString(String) - Method in class com.github.javacliparser.StringOption
-
- setValueViaCLIString(String) - Method in class moa.options.AbstractClassOption
-
- setValueViaCLIString(String) - Method in class moa.options.ClassOption
-
- setValueViaCLIString(String) - Method in class moa.options.ClassOptionWithListenerOption
-
- setValueViaCLIString(String) - Method in class moa.options.ClassOptionWithNames
-
- setValueViaCLIString(String) - Method in class moa.options.WEKAClassOption
-
- setVariance(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDBlock
-
- setVariance(double) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- setViaCLIString(String) - Method in class com.github.javacliparser.Options
-
- setViewport(JViewport) - Method in class moa.gui.visualization.GraphCanvas
-
- setVirtualChildren(AutoExpandVector<Iadem2.VirtualNode>) - Method in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- setVisible(boolean) - Method in class moa.gui.experimentertab.PreviewExperiments
-
- setVisited() - Method in class moa.clusterers.macro.dbscan.DenseMicroCluster
-
- setVisited(boolean) - Method in class moa.clusterers.dstream.DensityGrid
-
- setVisualizer(RunOutlierVisualizer) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- setVote(double[]) - Method in class moa.classifiers.rules.core.voting.Vote
-
- setVote(int, int, double) - Method in class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- setVote(int, int, double) - Method in interface com.yahoo.labs.samoa.instances.Prediction
-
Sets the vote for class of a given output attribute
- setVote(Prediction) - Method in class moa.classifiers.rules.multilabel.core.voting.MultiLabelVote
-
- setVotes(double[]) - Method in class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- setVotes(double[]) - Method in interface com.yahoo.labs.samoa.instances.Prediction
-
Sets the votes for the first output attribute
- setVotes(int, double[]) - Method in class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- setVotes(int, double[]) - Method in interface com.yahoo.labs.samoa.instances.Prediction
-
Sets the votes for a given output attribute
- setW(int) - Method in class moa.classifiers.core.driftdetection.ADWIN
-
- setWaitWinFull(boolean) - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- setWeight(double) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Sets the weight.
- setWeight(double) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
Sets the weight.
- setWeight(double) - Method in class moa.cluster.SphereCluster
-
- setWeight(double) - Method in interface moa.core.Example
-
- setWeight(double) - Method in class moa.core.InstanceExample
-
- setWeights(double[]) - Method in class moa.classifiers.rules.functions.Perceptron
-
- setWeights(double[][]) - Method in class moa.classifiers.functions.Perceptron
-
- setWeightSeenAtLastSplitEvaluation(double) - Method in class moa.classifiers.trees.EFDT.ActiveLearningNode
-
- setWeightSeenAtLastSplitEvaluation(double) - Method in class moa.classifiers.trees.HoeffdingOptionTree.ActiveLearningNode
-
- setWeightSeenAtLastSplitEvaluation(double) - Method in class moa.classifiers.trees.HoeffdingTree.ActiveLearningNode
-
- setWidth(int) - Method in class moa.classifiers.core.driftdetection.SEEDChangeDetector.SEEDWindow
-
- setWidth(int) - Method in class moa.gui.experimentertab.ImageChart
-
Set chart width.
- setWindowSize(int) - Method in class moa.gui.featureanalysis.FeatureImportancePanel
-
- setWindowSize(int) - Method in class moa.tasks.FeatureImportanceConfig
-
- setXMaxValue(int) - Method in class moa.gui.visualization.GraphAxes
-
- setXResolution(double) - Method in class moa.gui.visualization.AbstractGraphAxes
-
Sets the x resolution.
- setXResolution(double) - Method in class moa.gui.visualization.AbstractGraphPlot
-
Sets the resolution on the x-axis
- setXResolution(double) - Method in class moa.gui.visualization.GraphAxes
-
- setYMinMaxValues(double, double) - Method in class moa.gui.visualization.GraphAxes
-
- setYMinMaxValues(double, double) - Method in class moa.gui.visualization.GraphCurve
-
- setYResolution(double) - Method in class moa.gui.visualization.AbstractGraphAxes
-
Sets the y resolution
- setZoom(int, int, int, JScrollPane) - Method in class moa.gui.visualization.StreamOutlierPanel
-
- setZoom(int, int, int, JScrollPane) - Method in class moa.gui.visualization.StreamPanel
-
- SGD - Class in moa.classifiers.functions
-
Implements stochastic gradient descent for learning various linear models (binary class SVM, binary class logistic regression and linear regression).
- SGD() - Constructor for class moa.classifiers.functions.SGD
-
- SGDMultiClass - Class in moa.classifiers.functions
-
Implements stochastic gradient descent for learning various linear models (binary class SVM, binary class logistic regression and linear regression).
- SGDMultiClass() - Constructor for class moa.classifiers.functions.SGDMultiClass
-
- shafferTest() - Method in class moa.gui.experimentertab.statisticaltests.StatisticalTest
-
Return the p-values computed by the Shaffer test.
- shallowClear() - Method in class moa.clusterers.clustree.Entry
-
Clear the data and the buffer Custer in this
entry.
- showEditOptionsDialog(Component, String, OptionHandler) - Static method in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- showErrorDialog(Component, String, String) - Static method in class moa.gui.GUIUtils
-
- showExceptionDialog(Component, String, Exception) - Static method in class moa.gui.GUIUtils
-
- showHelpDialog() - Method in class com.github.javacliparser.gui.OptionsConfigurationPanel
-
- ShowProgress(String) - Method in interface moa.clusterers.outliers.MyBaseOutlierDetector.ProgressInfo
-
- ShowProgress(String) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- ShowProgress(String, boolean) - Method in class moa.clusterers.outliers.MyBaseOutlierDetector
-
- showSelectClassDialog(Component, String, Class<?>, String, String) - Static method in class moa.gui.ClassOptionSelectionPanel
-
- showSelectClassDialog(Component, String, Class<?>, String, String, String[]) - Static method in class moa.gui.ClassOptionWithNamesSelectionPanel
-
- showSummary() - Method in class moa.gui.experimentertab.Summary
-
The summaries are performed for each measure to be displayed in the user interface
- shuffleRandomSeedOption - Variable in class moa.tasks.CacheShuffledStream
-
- sigma - Variable in class moa.streams.generators.HyperplaneGenerator
-
- sigmaPercentageOption - Variable in class moa.streams.generators.HyperplaneGenerator
-
- sigmoidCrossingPointOption - Variable in class moa.classifiers.meta.LearnNSE
-
- sigmoidSlopeOption - Variable in class moa.classifiers.meta.LearnNSE
-
- SilhouetteCoefficient - Class in moa.evaluation
-
- SilhouetteCoefficient() - Constructor for class moa.evaluation.SilhouetteCoefficient
-
- silhouetteOption - Variable in class moa.tasks.EvaluateClustering
-
- silhouetteOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- similarityBetweenDistributionsOption - Variable in class moa.classifiers.meta.RCD
-
- SimpleBudget - Class in moa.clusterers.clustree.util
-
- SimpleBudget(int) - Constructor for class moa.clusterers.clustree.util.SimpleBudget
-
- SimpleCOD - Class in moa.clusterers.outliers.SimpleCOD
-
- SimpleCOD() - Constructor for class moa.clusterers.outliers.SimpleCOD.SimpleCOD
-
- SimpleCODBase - Class in moa.clusterers.outliers.SimpleCOD
-
- SimpleCODBase() - Constructor for class moa.clusterers.outliers.SimpleCOD.SimpleCODBase
-
- SimpleCODBase.EventItem - Class in moa.clusterers.outliers.SimpleCOD
-
- SimpleCODBase.EventQueue - Class in moa.clusterers.outliers.SimpleCOD
-
- SimpleCSVStream - Class in moa.streams.clustering
-
Provides a simple input stream for csv files.
- SimpleCSVStream() - Constructor for class moa.streams.clustering.SimpleCSVStream
-
Creates a simple ClusteringStream for csv files.
- SimpleEstimator() - Constructor for class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.SimpleEstimator
-
- SimpleEstimator() - Constructor for class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.SimpleEstimator
-
- SineGenerator - Class in moa.streams.generators
-
1.SINE1.
- SineGenerator() - Constructor for class moa.streams.generators.SineGenerator
-
- SineGenerator.ClassFunction - Interface in moa.streams.generators
-
- SINGLE_THREAD - Static variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- SingleClassifierDrift - Class in moa.classifiers.drift
-
Class for handling concept drift datasets with a wrapper on a
classifier.
- SingleClassifierDrift() - Constructor for class moa.classifiers.drift.SingleClassifierDrift
-
- SingleVector - Class in moa.classifiers.rules.multilabel.attributeclassobservers
-
Vector of float numbers with some utilities.
- SingleVector() - Constructor for class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- SingleVector(double[]) - Constructor for class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- SingleVector(float[]) - Constructor for class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- SingleVector(SingleVector) - Constructor for class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- size - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- size() - Method in class com.yahoo.labs.samoa.instances.Instances
-
- size() - Method in class com.yahoo.labs.samoa.instances.MultiLabelPrediction
-
- size() - Method in interface com.yahoo.labs.samoa.instances.Prediction
-
The size of the prediction, that is the number of output attributes
- size() - Method in class moa.classifiers.lazy.neighboursearch.NearestNeighbourSearch.MyHeap
-
returns the size of the heap.
- size() - Method in class moa.cluster.Clustering
-
- size() - Method in class moa.clusterers.kmeanspm.CuckooHashing
-
Returns the number of elements in the hash table.
- size() - Method in class moa.clusterers.outliers.AnyOut.util.DataSet
-
Returns the size of the set.
- size() - Method in class moa.recommender.rc.utils.DenseVector
-
- size() - Method in class moa.recommender.rc.utils.SparseVector
-
- size() - Method in class moa.recommender.rc.utils.Vector
-
- sizeCoresetOption - Variable in class moa.clusterers.streamkm.StreamKM
-
- sizeLimitOption - Variable in class moa.classifiers.oneclass.HSTrees
-
- sizeOf(Object) - Static method in class moa.core.SizeOf
-
Returns the size of the object.
- SizeOf - Class in moa.core
-
- SizeOf() - Constructor for class moa.core.SizeOf
-
- sizeTable - Variable in class moa.streams.generators.TextGenerator
-
- SizeWindow - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator.Estimator
-
- SizeWindow - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator.Estimator
-
- SizeWindow - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator.WindowEstimator
-
- SizeWindow - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
-
- skewOption - Variable in class moa.streams.generators.multilabel.MetaMultilabelGenerator
-
- skip(long) - Method in class moa.core.InputStreamProgressMonitor
-
- skipIdenticalTipText() - Method in class moa.classifiers.lazy.neighboursearch.LinearNNSearch
-
Returns the tip text for this property.
- skipInLevelCount() - Method in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- skipInLevelCount() - Method in class moa.classifiers.trees.ARFFIMTDD.LeafNode
-
- skipInLevelCount() - Method in class moa.classifiers.trees.ARFFIMTDD.Node
-
- skipInLevelCount() - Method in class moa.classifiers.trees.FIMTDD.LeafNode
-
- skipInLevelCount() - Method in class moa.classifiers.trees.FIMTDD.Node
-
- skipInLevelCount() - Method in class moa.classifiers.trees.ORTO.OptionNode
-
- skipStackingOption - Variable in class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- slider - Variable in class com.github.javacliparser.gui.FloatOptionEditComponent
-
- slider - Variable in class com.github.javacliparser.gui.IntOptionEditComponent
-
- SLIDER_RESOLUTION - Static variable in class com.github.javacliparser.gui.FloatOptionEditComponent
-
- SliderPanel() - Constructor for class moa.gui.experimentertab.RankingGraph.SliderPanel
-
Constructor.
- sliderValueToFloatValue(int) - Method in class com.github.javacliparser.gui.FloatOptionEditComponent
-
- SlidingMidPointOfWidestSide - Class in moa.classifiers.lazy.neighboursearch.kdtrees
-
The class that splits a node into two based on the midpoint value of the dimension in which the node's rectangle is widest.
- SlidingMidPointOfWidestSide() - Constructor for class moa.classifiers.lazy.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
-
- slidingWindowSize - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- slidingWindowSize - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- slidingWindowStep - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- slidingWindowStep - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- slope - Variable in class moa.classifiers.meta.LearnNSE
-
- sm(double, double) - Static method in class moa.core.Utils
-
Tests if a is smaller than b.
- SMALL - Static variable in class moa.core.Utils
-
The small deviation allowed in double comparisons.
- smoothingOption - Variable in class moa.classifiers.meta.OCBoost
-
- smoothOption - Variable in class moa.tasks.Plot
-
Determines whether to smooth the plot with bezier curves.
- smOrEq(double, double) - Static method in class moa.core.Utils
-
Tests if a is smaller or equal to b.
- sort(double[]) - Static method in class moa.core.Utils
-
Sorts a given array of doubles in ascending order and returns an
array of integers with the positions of the elements of the
original array in the sorted array.
- sort(int[]) - Static method in class moa.core.Utils
-
Sorts a given array of integers in ascending order and returns an
array of integers with the positions of the elements of the original
array in the sorted array.
- sortByValue(Map<K, V>) - Static method in class moa.streams.filters.ReplacingMissingValuesFilter.MapUtil
-
- sortedScores - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.Estimator
-
- sortedScores - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.Estimator
-
- sourceInstanceToTarget(Instance) - Method in class moa.classifiers.rules.multilabel.instancetransformers.InstanceAttributesSelector
-
- sourceInstanceToTarget(Instance) - Method in class moa.classifiers.rules.multilabel.instancetransformers.InstanceOutputAttributesSelector
-
- sourceInstanceToTarget(Instance) - Method in interface moa.classifiers.rules.multilabel.instancetransformers.InstanceTransformer
-
- sourceInstanceToTarget(Instance) - Method in class moa.classifiers.rules.multilabel.instancetransformers.NoInstanceTransformation
-
- sp - Variable in class moa.gui.visualization.PointPanel
-
- SparseInstance - Class in com.yahoo.labs.samoa.instances
-
The Class SparseInstance.
- SparseInstance(double) - Constructor for class com.yahoo.labs.samoa.instances.SparseInstance
-
Instantiates a new sparse instance.
- SparseInstance(double, double[]) - Constructor for class com.yahoo.labs.samoa.instances.SparseInstance
-
Instantiates a new sparse instance.
- SparseInstance(double, double[], int[], int) - Constructor for class com.yahoo.labs.samoa.instances.SparseInstance
-
Instantiates a new sparse instance.
- SparseInstance(InstanceImpl) - Constructor for class com.yahoo.labs.samoa.instances.SparseInstance
-
Instantiates a new sparse instance.
- SparseInstanceData - Class in com.yahoo.labs.samoa.instances
-
The Class SparseInstanceData.
- SparseInstanceData(double[], int[], int) - Constructor for class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Instantiates a new sparse instance data.
- SparseInstanceData(int) - Constructor for class com.yahoo.labs.samoa.instances.SparseInstanceData
-
Instantiates a new sparse instance data.
- SparseVector - Class in moa.recommender.rc.utils
-
- SparseVector() - Constructor for class moa.recommender.rc.utils.SparseVector
-
- SparseVector(Map<Integer, Double>) - Constructor for class moa.recommender.rc.utils.SparseVector
-
- SparseVector.SparseVectorIterator - Class in moa.recommender.rc.utils
-
- SparseVectorIterator() - Constructor for class moa.recommender.rc.utils.SparseVector.SparseVectorIterator
-
- speedCentroids - Variable in class moa.streams.generators.RandomRBFGeneratorDrift
-
- speedChangeOption - Variable in class moa.streams.generators.RandomRBFGeneratorDrift
-
- speedOption - Variable in class moa.clusterers.denstream.WithDBSCAN
-
- speedOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- speedRangeOption - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- SPegasos - Class in moa.classifiers.functions
-
Implements the stochastic variant of the Pegasos
(Primal Estimated sub-GrAdient SOlver for SVM) method of Shalev-Shwartz et
al.
- SPegasos() - Constructor for class moa.classifiers.functions.SPegasos
-
- SphereCluster - Class in moa.cluster
-
A simple implementation of the Cluster interface representing
spherical clusters.
- SphereCluster() - Constructor for class moa.cluster.SphereCluster
-
- SphereCluster(double[], double) - Constructor for class moa.cluster.SphereCluster
-
- SphereCluster(double[], double, double) - Constructor for class moa.cluster.SphereCluster
-
- SphereCluster(int, double, Random) - Constructor for class moa.cluster.SphereCluster
-
- SphereCluster(List<? extends Instance>, int) - Constructor for class moa.cluster.SphereCluster
-
- spinner - Variable in class com.github.javacliparser.gui.FloatOptionEditComponent
-
- spinner - Variable in class com.github.javacliparser.gui.IntOptionEditComponent
-
- split - Variable in class moa.classifiers.trees.iadem.Iadem2.LeafNode
-
- split() - Method in class moa.classifiers.rules.core.Rule
-
- SPLIT_BY_TIE_BREAKING - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- SPLIT_WITH_CONFIDENCE - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- splitAttIndex - Variable in class moa.streams.generators.RandomTreeGenerator.Node
-
- splitAttValue - Variable in class moa.streams.generators.RandomTreeGenerator.Node
-
- splitCharOption - Variable in class moa.streams.clustering.SimpleCSVStream
-
- splitConfidenceOption - Variable in class moa.classifiers.multilabel.trees.ISOUPTree
-
- splitConfidenceOption - Variable in class moa.classifiers.rules.AbstractAMRules
-
- splitConfidenceOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- splitConfidenceOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- splitConfidenceOption - Variable in class moa.classifiers.rules.RuleClassifier
-
- splitConfidenceOption - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- splitConfidenceOption - Variable in class moa.classifiers.trees.EFDT
-
- splitConfidenceOption - Variable in class moa.classifiers.trees.FIMTDD
-
- splitConfidenceOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- splitConfidenceOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- splitConfidenceOption - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- splitCount - Variable in class moa.classifiers.trees.EFDT
-
- splitCriterion - Variable in class moa.classifiers.rules.multilabel.core.LearningLiteral
-
- SplitCriterion - Interface in moa.classifiers.core.splitcriteria
-
Interface for computing splitting criteria.
- splitCriterionOption - Variable in class moa.classifiers.rules.AMRulesRegressorOld
-
- splitCriterionOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- splitCriterionOption - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- splitCriterionOption - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- splitCriterionOption - Variable in class moa.classifiers.trees.DecisionStump
-
- splitCriterionOption - Variable in class moa.classifiers.trees.EFDT
-
- splitCriterionOption - Variable in class moa.classifiers.trees.FIMTDD
-
- splitCriterionOption - Variable in class moa.classifiers.trees.HoeffdingOptionTree
-
- splitCriterionOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- splitCriterionOption - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- splitFunction - Variable in class moa.clusterers.outliers.utils.mtree.MTree
-
- SplitFunction<DATA> - Interface in moa.clusterers.outliers.utils.mtree
-
Defines an object to be used to split a node in an M-Tree.
- SplitFunction.SplitResult<DATA> - Class in moa.clusterers.outliers.utils.mtree
-
- splitIndex - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- splitNode(KDTreeNode, int, double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KDTreeNodeSplitter
-
Splits a node into two.
- splitNode(KDTreeNode, int, double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.KMeansInpiredMethod
-
Splits a node into two such that the overall sum of squared distances
of points to their centres on both sides of the (axis-parallel)
splitting plane is minimum.
- splitNode(KDTreeNode, int, double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MedianOfWidestDimension
-
Splits a node into two based on the median value of the dimension
in which the points have the widest spread.
- splitNode(KDTreeNode, int, double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.MidPointOfWidestDimension
-
Splits a node into two based on the midpoint value of the dimension
in which the points have the widest spread.
- splitNode(KDTreeNode, int, double[][], double[][]) - Method in class moa.classifiers.lazy.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
-
Splits a node into two based on the midpoint value of the dimension
in which the node's rectangle is widest.
- SplitNode(InstanceConditionalTest, double[]) - Constructor for class moa.classifiers.trees.EFDT.SplitNode
-
- SplitNode(InstanceConditionalTest, double[]) - Constructor for class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- SplitNode(InstanceConditionalTest, double[]) - Constructor for class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- SplitNode(InstanceConditionalTest, double[], int) - Constructor for class moa.classifiers.trees.EFDT.SplitNode
-
- SplitNode(InstanceConditionalTest, double[], int) - Constructor for class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- SplitNode(InstanceConditionalTest, ARFFIMTDD) - Constructor for class moa.classifiers.trees.ARFFIMTDD.SplitNode
-
Create a new SplitNode
- SplitNode(InstanceConditionalTest, FIMTDD) - Constructor for class moa.classifiers.trees.FIMTDD.SplitNode
-
Create a new SplitNode
- SplitNode(Predicate, ISOUPTree) - Constructor for class moa.classifiers.multilabel.trees.ISOUPTree.SplitNode
-
Create a new SplitNode
- SplitNode(Iadem2, Iadem2.Node, Iadem2.Node[], double[], InstanceConditionalTest) - Constructor for class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- splitNodeCount - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- splitNodeCount - Variable in class moa.classifiers.trees.FIMTDD
-
- splitNodes(KDTreeNode, double[][], int) - Method in class moa.classifiers.lazy.neighboursearch.KDTree
-
Recursively splits nodes of a tree starting from the supplied node.
- splitOptions(String) - Static method in class moa.core.Utils
-
Split up a string containing options into an array of strings,
one for each option.
- splitParameterFromRemainingOptions(String) - Static method in class com.github.javacliparser.Options
-
Internal method that splits a string into two parts - the parameter for
the current option, and the remaining options.
- SplitResult(Pair<DATA>, Pair<Set<DATA>>) - Constructor for class moa.clusterers.outliers.utils.mtree.SplitFunction.SplitResult
-
- splitTest - Variable in class moa.classifiers.core.AttributeSplitSuggestion
-
- splitTest - Variable in class moa.classifiers.trees.ARFFIMTDD.SplitNode
-
- splitTest - Variable in class moa.classifiers.trees.EFDT.SplitNode
-
- splitTest - Variable in class moa.classifiers.trees.FIMTDD.SplitNode
-
- splitTest - Variable in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- splitTest - Variable in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- splitTest - Variable in class moa.classifiers.trees.iadem.Iadem2.SplitNode
-
- splitTestsOption - Variable in class moa.classifiers.trees.iadem.Iadem2
-
- sqDifference(int, double, double) - Method in class moa.classifiers.lazy.neighboursearch.EuclideanDistance
-
Returns the squared difference of two values of an attribute.
- SQRTH - Static variable in class moa.core.Statistics
-
- SQTPI - Static variable in class moa.core.Statistics
-
- squared_radius() - Method in class moa.cluster.Miniball
-
Return the sqaured Radius of the miniball
- squaredActualClassStatistics - Variable in class moa.classifiers.rules.RuleClassification
-
- squaredAttributeStatistics - Variable in class moa.classifiers.rules.RuleClassification
-
- squaredAttributeStatisticsSupervised - Variable in class moa.classifiers.rules.RuleClassification
-
- SQUAREDLOSS - Static variable in class moa.classifiers.functions.SGD
-
- SQUAREDLOSS - Static variable in class moa.classifiers.functions.SGDMultiClass
-
- squaredperceptronattributeStatistics - Variable in class moa.classifiers.rules.functions.Perceptron
-
- squaredperceptronsumY - Variable in class moa.classifiers.rules.functions.Perceptron
-
- squareError - Variable in class moa.evaluation.BasicMultiTargetPerformanceEvaluator
-
- squareError - Variable in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- squareError - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- squareError - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator
-
- squareError - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- squareError - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator
-
- squareErrorToTargetMean - Variable in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- squareErrorToTargetMean - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- squareTargetError - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- SS - Variable in class moa.cluster.CFCluster
-
Squared sum of all the points added to the cluster.
- SSQ - Class in moa.evaluation
-
- SSQ() - Constructor for class moa.evaluation.SSQ
-
- ssqOption - Variable in class moa.tasks.EvaluateClustering
-
- ssqOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- SST - Variable in class moa.clusterers.clustream.ClustreamKernel
-
- stabIndexSizeOption - Variable in class moa.classifiers.meta.ADACC
-
Threshold for the stability index
- stableLearner - Variable in class moa.classifiers.meta.PairedLearners
-
- stableLearnerOption - Variable in class moa.classifiers.meta.PairedLearners
-
- stableSort(double[]) - Static method in class moa.core.Utils
-
Sorts a given array of doubles in ascending order and returns an
array of integers with the positions of the elements of the original
array in the sorted array.
- stabPeriodOption - Variable in class moa.streams.RecurrentConceptDriftStream
-
- StackedPredictor - Class in moa.classifiers.rules.multilabel.functions
-
- StackedPredictor() - Constructor for class moa.classifiers.rules.multilabel.functions.StackedPredictor
-
- STAGGERGenerator - Class in moa.streams.generators
-
Stream generator for STAGGER Concept functions.
- STAGGERGenerator() - Constructor for class moa.streams.generators.STAGGERGenerator
-
- STAGGERGenerator.ClassFunction - Interface in moa.streams.generators
-
- StandardTaskMonitor - Class in moa.tasks
-
Class that represents a standard task monitor.
- StandardTaskMonitor() - Constructor for class moa.tasks.StandardTaskMonitor
-
- startIndexValidation(int) - Method in class moa.gui.featureanalysis.VisualizeFeaturesPanel
-
- state - Variable in class moa.classifiers.rules.core.conditionaltests.NominalAttributeBinaryRulePredicate
-
- state - Variable in class moa.classifiers.rules.core.conditionaltests.NumericAttributeBinaryRulePredicate
-
- stateChanged(ChangeEvent) - Method in class moa.options.DependentOptionsUpdater
-
- StatisticalCollection - Class in moa.evaluation
-
- StatisticalCollection() - Constructor for class moa.evaluation.StatisticalCollection
-
- statisticalOption - Variable in class moa.tasks.EvaluateClustering
-
- statisticalOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- StatisticalTest - Class in moa.gui.experimentertab.statisticaltests
-
- StatisticalTest - Interface in moa.classifiers.core.statisticaltests
-
This interface represents how to perform multivariate statistical tests.
- StatisticalTest(List<Stream>) - Constructor for class moa.gui.experimentertab.statisticaltests.StatisticalTest
-
Constructor.
- statisticalTestOption - Variable in class moa.classifiers.meta.RCD
-
- statistics - Variable in class moa.classifiers.rules.AbstractAMRules
-
- statistics - Variable in class moa.classifiers.rules.core.Rule.Builder
-
- statistics - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearner
-
- statistics - Variable in class moa.classifiers.rules.multilabel.AMRulesMultiLabelLearnerSemiSuper
-
- statistics(double[]) - Method in class moa.classifiers.rules.core.Rule.Builder
-
- Statistics - Class in moa.core
-
Class implementing some distributions, tests, etc.
- Statistics() - Constructor for class moa.core.Statistics
-
- statisticsBranchSplit - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- statisticsByNominalValue - Variable in class moa.classifiers.rules.multilabel.attributeclassobservers.MultiLabelNominalAttributeObserver
-
- statisticsNewRuleActiveLearningNode - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- statisticsOtherBranchSplit - Variable in class moa.classifiers.rules.core.RuleActiveLearningNode
-
- statisticsOtherBranchSplit() - Method in class moa.classifiers.rules.core.Rule
-
- stdDev - Variable in class moa.streams.generators.RandomRBFGenerator.Centroid
-
- StdDevThreshold - Class in moa.classifiers.rules.multilabel.outputselectors
-
- StdDevThreshold() - Constructor for class moa.classifiers.rules.multilabel.outputselectors.StdDevThreshold
-
- StdPrintMsg() - Constructor for class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
-
- StdPrintMsg(String) - Constructor for class moa.clusterers.outliers.MyBaseOutlierDetector.StdPrintMsg
-
- STEPD - Class in moa.classifiers.core.driftdetection
-
- STEPD() - Constructor for class moa.classifiers.core.driftdetection.STEPD
-
- stepOption - Variable in class moa.classifiers.active.ALUncertainty
-
- STEPS - moa.gui.experimentertab.PlotTab.PlotStyle
-
- STEPS - moa.tasks.Plot.PlotStyle
-
- stirlingFormula(double) - Static method in class moa.core.Statistics
-
Returns the Gamma function computed by Stirling's formula.
- stop() - Method in class moa.gui.visualization.RunOutlierVisualizer
-
- stop() - Method in class moa.gui.visualization.RunVisualizer
-
- stopMemManagementOption - Variable in class moa.classifiers.trees.EFDT
-
- stopMemManagementOption - Variable in class moa.classifiers.trees.HoeffdingTree
-
- stopRun() - Method in class moa.gui.clustertab.ClusteringSetupTab
-
- stopRun() - Method in class moa.gui.outliertab.OutlierSetupTab
-
- stopVisualizer() - Method in class moa.gui.clustertab.ClusteringVisualTab
-
- stopVisualizer() - Method in class moa.gui.outliertab.OutlierVisualTab
-
- storedCountOption - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
Number of classifiers remembered and available for ensemble construction.
- storedLearners - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
- storedWeights - Variable in class moa.classifiers.meta.AccuracyWeightedEnsemble
-
The weights of stored classifiers.
- STORMBase - Class in moa.clusterers.outliers.Angiulli
-
- STORMBase() - Constructor for class moa.clusterers.outliers.Angiulli.STORMBase
-
- stratify(int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Stratify.
- stratStep(int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
- stream - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- stream - Variable in class moa.tasks.WriteMultipleStreamsToARFF
-
- Stream - Class in moa.gui.experimentertab
-
This class contains the name of a stream and a list of algorithms.
- Stream(String, List<String>, List<String>, List<Measure>) - Constructor for class moa.gui.experimentertab.Stream
-
Stream Constructor
- StreamFilter - Interface in moa.streams.filters
-
Interface representing a stream filter.
- streamHeader - Variable in class com.yahoo.labs.samoa.instances.ArffLoader
-
- streamHeader - Variable in class moa.streams.clustering.RandomRBFGeneratorEvents
-
- streamHeader - Variable in class moa.streams.ConceptDriftRealStream
-
- streamHeader - Variable in class moa.streams.filters.RemoveDiscreteAttributeFilter
-
- streamHeader - Variable in class moa.streams.generators.AgrawalGenerator
-
- streamHeader - Variable in class moa.streams.generators.AssetNegotiationGenerator
-
- streamHeader - Variable in class moa.streams.generators.cd.AbstractConceptDriftGenerator
-
- streamHeader - Variable in class moa.streams.generators.HyperplaneGenerator
-
- streamHeader - Variable in class moa.streams.generators.LEDGenerator
-
- streamHeader - Variable in class moa.streams.generators.MixedGenerator
-
- streamHeader - Variable in class moa.streams.generators.RandomRBFGenerator
-
- streamHeader - Variable in class moa.streams.generators.RandomTreeGenerator
-
- streamHeader - Variable in class moa.streams.generators.SEAGenerator
-
- streamHeader - Variable in class moa.streams.generators.SineGenerator
-
- streamHeader - Variable in class moa.streams.generators.STAGGERGenerator
-
- streamHeader - Variable in class moa.streams.generators.TextGenerator
-
- streamHeader - Variable in class moa.streams.generators.WaveformGenerator
-
- StreamingRandomPatches - Class in moa.classifiers.meta
-
Streaming Random Patches
- StreamingRandomPatches() - Constructor for class moa.classifiers.meta.StreamingRandomPatches
-
- StreamingRandomPatches.StreamingRandomPatchesClassifier - Class in moa.classifiers.meta
-
- StreamingRandomPatchesClassifier(int, Classifier, BasicClassificationPerformanceEvaluator, long, boolean, boolean, ClassOption, ClassOption, boolean) - Constructor for class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- StreamingRandomPatchesClassifier(int, Classifier, BasicClassificationPerformanceEvaluator, long, boolean, boolean, ClassOption, ClassOption, ArrayList<Integer>, Instance, boolean) - Constructor for class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- StreamKM - Class in moa.clusterers.streamkm
-
- StreamKM() - Constructor for class moa.clusterers.streamkm.StreamKM
-
- streamModel - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- StreamObj - Class in moa.clusterers.outliers.AbstractC
-
- StreamObj - Class in moa.clusterers.outliers.Angiulli
-
- StreamObj - Class in moa.clusterers.outliers.MCOD
-
- StreamObj - Class in moa.clusterers.outliers.SimpleCOD
-
- StreamObj(double...) - Constructor for class moa.clusterers.outliers.AbstractC.StreamObj
-
- StreamObj(double...) - Constructor for class moa.clusterers.outliers.Angiulli.StreamObj
-
- StreamObj(double...) - Constructor for class moa.clusterers.outliers.MCOD.StreamObj
-
- StreamObj(double...) - Constructor for class moa.clusterers.outliers.SimpleCOD.StreamObj
-
- streamOption - Variable in class moa.streams.BootstrappedStream
-
- streamOption - Variable in class moa.streams.ConceptDriftRealStream
-
- streamOption - Variable in class moa.streams.ConceptDriftStream
-
- streamOption - Variable in class moa.streams.FilteredStream
-
- streamOption - Variable in class moa.streams.ImbalancedStream
-
- streamOption - Variable in class moa.streams.IrrelevantFeatureAppenderStream
-
- streamOption - Variable in class moa.streams.MultiFilteredStream
-
- streamOption - Variable in class moa.streams.MultiLabelFilteredStream
-
- streamOption - Variable in class moa.streams.PartitioningStream
-
- streamOption - Variable in class moa.tasks.CacheShuffledStream
-
- streamOption - Variable in class moa.tasks.EvaluateClustering
-
- streamOption - Variable in class moa.tasks.EvaluateConceptDrift
-
- streamOption - Variable in class moa.tasks.EvaluateInterleavedChunks
-
Allows to select the stream the classifier will learn.
- streamOption - Variable in class moa.tasks.EvaluateInterleavedTestThenTrain
-
- streamOption - Variable in class moa.tasks.EvaluateModel
-
- streamOption - Variable in class moa.tasks.EvaluateModelMultiLabel
-
- streamOption - Variable in class moa.tasks.EvaluateModelMultiTarget
-
- streamOption - Variable in class moa.tasks.EvaluateModelRegression
-
- streamOption - Variable in class moa.tasks.EvaluateMultipleClusterings
-
- streamOption - Variable in class moa.tasks.EvaluatePeriodicHeldOutTest
-
- streamOption - Variable in class moa.tasks.EvaluatePrequential
-
- streamOption - Variable in class moa.tasks.EvaluatePrequentialCV
-
- streamOption - Variable in class moa.tasks.EvaluatePrequentialDelayed
-
- streamOption - Variable in class moa.tasks.EvaluatePrequentialDelayedCV
-
- streamOption - Variable in class moa.tasks.EvaluatePrequentialMultiLabel
-
- streamOption - Variable in class moa.tasks.EvaluatePrequentialMultiTarget
-
- streamOption - Variable in class moa.tasks.EvaluatePrequentialMultiTargetSemiSuper
-
- streamOption - Variable in class moa.tasks.EvaluatePrequentialRegression
-
- streamOption - Variable in class moa.tasks.LearnModel
-
- streamOption - Variable in class moa.tasks.LearnModelMultiLabel
-
- streamOption - Variable in class moa.tasks.LearnModelMultiTarget
-
- streamOption - Variable in class moa.tasks.LearnModelRegression
-
- streamOption - Variable in class moa.tasks.MeasureStreamSpeed
-
- streamOption - Variable in class moa.tasks.meta.ALPrequentialEvaluationTask
-
- streamOption - Variable in class moa.tasks.WriteMultipleStreamsToARFF
-
- streamOption - Variable in class moa.tasks.WriteStreamToARFFFile
-
- StreamOutlierPanel - Class in moa.gui.visualization
-
- StreamOutlierPanel(Color) - Constructor for class moa.gui.visualization.StreamOutlierPanel
-
- streamPanel - Variable in class moa.gui.visualization.ClusterPanel
-
- streamPanel - Variable in class moa.gui.visualization.OutlierPanel
-
- StreamPanel - Class in moa.gui.visualization
-
- StreamPanel() - Constructor for class moa.gui.visualization.StreamPanel
-
Creates new form StreamPanel
- streamParameterOption - Variable in class moa.tasks.RunStreamTasks
-
- streamPos - Variable in class moa.streams.CachedInstancesStream
-
- streams - Variable in class moa.gui.experimentertab.statisticaltests.StatisticalTest
-
- streams - Variable in class moa.gui.experimentertab.Summary
-
The list of the streams
- streamTokenizer - Variable in class com.yahoo.labs.samoa.instances.ArffLoader
-
The stream tokenizer.
- StringOption - Class in com.github.javacliparser
-
String option.
- StringOption(String, char, String, String) - Constructor for class com.github.javacliparser.StringOption
-
- StringOptionEditComponent - Class in com.github.javacliparser.gui
-
An OptionEditComponent that lets the user edit a string option.
- StringOptionEditComponent(Option) - Constructor for class com.github.javacliparser.gui.StringOptionEditComponent
-
- StringUtils - Class in com.github.javacliparser
-
Class implementing some string utility methods.
- StringUtils - Class in moa.core
-
Class implementing some string utility methods.
- StringUtils() - Constructor for class com.github.javacliparser.StringUtils
-
- StringUtils() - Constructor for class moa.core.StringUtils
-
- stringValue(int) - Method in interface com.yahoo.labs.samoa.instances.Instance
-
Gets the value of a discrete attribute as a string.
- stringValue(int) - Method in class com.yahoo.labs.samoa.instances.InstanceImpl
-
String value.
- stringValues() - Static method in enum moa.capabilities.Capability
-
Creates an array of the string representation
of each value.
- stringWithoutHeader() - Method in class com.yahoo.labs.samoa.instances.Instances
-
Returns the instances in the dataset as a string in ARFF format.
- stripPackagePrefix(String, Class<?>) - Static method in class com.github.javacliparser.AbstractClassOption
-
Gets the class name without its package name prefix.
- stripPackagePrefix(String, Class<?>) - Static method in class moa.options.AbstractClassOption
-
Gets the class name without its package name prefix.
- structureChanged() - Method in class moa.gui.PreviewTableModel
-
- subset - Variable in class moa.classifiers.meta.StreamingRandomPatches.StreamingRandomPatchesClassifier
-
- subspaceModeOption - Variable in class moa.classifiers.meta.StreamingRandomPatches
-
- subspaces - Variable in class moa.classifiers.meta.StreamingRandomPatches
-
- subspaceSize - Variable in class moa.classifiers.meta.AdaptiveRandomForest
-
- subspaceSize - Variable in class moa.classifiers.meta.AdaptiveRandomForestRegressor
-
- subspaceSizeOption - Variable in class moa.classifiers.meta.StreamingRandomPatches
-
- subspaceSizeOption - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- subspaceSizeOption - Variable in class moa.classifiers.trees.ARFHoeffdingTree
-
- subtractValues(double[]) - Method in class moa.core.DoubleVector
-
- subtractValues(float[]) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- subtractValues(SingleVector) - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- subtractValues(DoubleVector) - Method in class moa.core.DoubleVector
-
- subtreeDepth() - Method in class moa.classifiers.trees.EFDT.Node
-
- subtreeDepth() - Method in class moa.classifiers.trees.EFDT.SplitNode
-
- subtreeDepth() - Method in class moa.classifiers.trees.HoeffdingOptionTree.Node
-
- subtreeDepth() - Method in class moa.classifiers.trees.HoeffdingOptionTree.SplitNode
-
- subtreeDepth() - Method in class moa.classifiers.trees.HoeffdingTree.Node
-
- subtreeDepth() - Method in class moa.classifiers.trees.HoeffdingTree.SplitNode
-
- subtreeList - Variable in class moa.classifiers.trees.iadem.Iadem3
-
- sum - Variable in class moa.classifiers.rules.functions.TargetMean
-
- sum - Variable in class moa.evaluation.BasicAUCImbalancedPerformanceEvaluator.SimpleEstimator
-
- sum - Variable in class moa.evaluation.BasicClassificationPerformanceEvaluator.BasicEstimator
-
- sum - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceEvaluator.Estimator
-
- sum - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator.Estimator
-
- sum - Variable in class moa.evaluation.WindowAUCImbalancedPerformanceEvaluator.SimpleEstimator
-
- sum - Variable in class moa.evaluation.WindowClassificationPerformanceEvaluator.WindowEstimator
-
- sum - Variable in class moa.evaluation.WindowRegressionPerformanceEvaluator.Estimator
-
- sum - Variable in class moa.learners.featureanalysis.ClassifierWithFeatureImportance
-
- sum(double[]) - Static method in class moa.core.Utils
-
Computes the sum of the elements of an array of doubles.
- sum(int[]) - Static method in class moa.core.Utils
-
Computes the sum of the elements of an array of integers.
- sum(long[]) - Method in class moa.classifiers.trees.iadem.IademGaussianNumericAttributeClassObserver
-
- sum(long[]) - Method in class moa.classifiers.trees.iadem.IademGreenwaldKhannaNumericAttributeClassObserver
-
- sumAbsolutError - Variable in class moa.classifiers.rules.driftdetection.PageHinkleyTest
-
- sumError - Variable in class moa.classifiers.rules.meta.RandomAMRulesOld
-
- sumError - Variable in class moa.classifiers.rules.multilabel.errormeasurers.MeanAbsoluteDeviationMT
-
- sumError - Variable in class moa.classifiers.rules.multilabel.errormeasurers.RelativeMeanAbsoluteDeviationMT
-
- sumErrorToTargetMean - Variable in class moa.classifiers.rules.multilabel.errormeasurers.RelativeMeanAbsoluteDeviationMT
-
- sumFreqTwitterGenerator - Variable in class moa.streams.generators.TextGenerator
-
- summary - Variable in class moa.core.GreenwaldKhannaQuantileSummary
-
- summary - Variable in class moa.gui.experimentertab.Summary
-
- summary - Variable in class moa.gui.experimentertab.SummaryViewer
-
- summary - Variable in class moa.gui.experimentertab.TaskManagerTabPanel
-
- Summary - Class in moa.gui.experimentertab
-
This class performs the different summaries.
- Summary(List<Stream>, String) - Constructor for class moa.gui.experimentertab.Summary
-
Summary Constructor
- summary1CMD(String[]) - Method in class moa.gui.experimentertab.ExperimeterCLI
-
- summaryCMD(String[], String[]) - Method in class moa.gui.experimentertab.SummaryTab
-
- SummaryTab - Class in moa.gui.experimentertab
-
Summarize the performance measurements of different learning algorithms over
time in LaTeX and HTML formats.
- SummaryTab() - Constructor for class moa.gui.experimentertab.SummaryTab
-
SummaryTab Constructor
- summaryTable - Variable in class moa.gui.experimentertab.SummaryViewer
-
- SummaryTable - Class in moa.gui.experimentertab
-
Class to create the fields needed to display the summaries in the gui.
- SummaryTable() - Constructor for class moa.gui.experimentertab.SummaryTable
-
- summaryType - Variable in class moa.gui.experimentertab.SummaryViewer
-
- SummaryViewer - Class in moa.gui.experimentertab
-
Class to display summaries in the gui.
- SummaryViewer(SummaryTable[], Summary, String) - Constructor for class moa.gui.experimentertab.SummaryViewer
-
Constructor.
- sumOfAbsErrors - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.InnerNode
-
- sumOfAbsErrors - Variable in class moa.classifiers.trees.ARFFIMTDD.Node
-
- sumOfAbsErrors - Variable in class moa.classifiers.trees.FIMTDD.Node
-
- sumOfAbsoluteValues() - Method in class moa.core.DoubleVector
-
- sumOfAttrSquares - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- sumOfAttrSquares - Variable in class moa.classifiers.trees.FIMTDD
-
- sumOfAttrValues - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- sumOfAttrValues - Variable in class moa.classifiers.trees.FIMTDD
-
- sumOfSquares - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- sumOfSquares - Variable in class moa.classifiers.trees.ARFFIMTDD.FIMTDDPerceptron
-
- sumOfSquares - Variable in class moa.classifiers.trees.ARFFIMTDD.Node
-
- sumOfSquares - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- sumOfSquares - Variable in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
-
- sumOfSquares - Variable in class moa.classifiers.trees.FIMTDD.Node
-
- sumOfSquares - Variable in class moa.classifiers.trees.FIMTDD
-
- sumOfValues - Variable in class moa.classifiers.multilabel.trees.ISOUPTree.Node
-
- sumOfValues - Variable in class moa.classifiers.trees.ARFFIMTDD.FIMTDDPerceptron
-
- sumOfValues - Variable in class moa.classifiers.trees.ARFFIMTDD.Node
-
- sumOfValues - Variable in class moa.classifiers.trees.ARFFIMTDD
-
- sumOfValues - Variable in class moa.classifiers.trees.FIMTDD.FIMTDDPerceptron
-
- sumOfValues - Variable in class moa.classifiers.trees.FIMTDD.Node
-
- sumOfValues - Variable in class moa.classifiers.trees.FIMTDD
-
- sumOfValues() - Method in class moa.classifiers.rules.multilabel.attributeclassobservers.SingleVector
-
- sumOfValues() - Method in class moa.core.DoubleVector
-
- sumRatings - Variable in class moa.recommender.rc.data.impl.MemRecommenderData
-
- sumSquaredError - Variable in class moa.classifiers.rules.multilabel.errormeasurers.RelativeRootMeanSquaredErrorMT
-
- sumSquaredErrorToTargetMean - Variable in class moa.classifiers.rules.multilabel.errormeasurers.RelativeRootMeanSquaredErrorMT
-
- sumTarget - Variable in class moa.evaluation.BasicRegressionPerformanceEvaluator
-
- sumVoteDistrib() - Method in class moa.classifiers.rules.core.voting.Vote
-
- sumVoteDistrib() - Method in class moa.classifiers.rules.multilabel.core.voting.MultiLabelVote
-
- sumY - Variable in class moa.classifiers.rules.multilabel.errormeasurers.RelativeMeanAbsoluteDeviationMT
-
- sumY - Variable in class moa.classifiers.rules.multilabel.errormeasurers.RelativeRootMeanSquaredErrorMT
-
- sumY - Variable in class moa.evaluation.BasicMultiTargetPerformanceRelativeMeasuresEvaluator
-
- sumY - Variable in class moa.evaluation.MultiTargetWindowRegressionPerformanceRelativeMeasuresEvaluator
-
- Supervised - Variable in class moa.classifiers.rules.RuleClassifier
-
- supportsCustomEditor() - Method in class weka.gui.MOAClassOptionEditor
-
Returns true because we do support a custom editor.
- suppressHeaderOption - Variable in class moa.tasks.WriteMultipleStreamsToARFF
-
- suppressHeaderOption - Variable in class moa.tasks.WriteStreamToARFFFile
-
- suppressIrrelevantAttributesOption - Variable in class moa.streams.generators.LEDGenerator
-
- suppressIrrelevantAttributesOption - Variable in class moa.streams.generators.SineGenerator
-
- SVG - moa.gui.experimentertab.PlotTab.Terminal
-
- SVG - moa.tasks.Plot.Terminal
-
- swap(int, int) - Method in class com.yahoo.labs.samoa.instances.Instances
-
Swap.
- switchedAlternateTrees - Variable in class moa.classifiers.trees.HoeffdingAdaptiveTree
-
- swms - Variable in class moa.classifiers.meta.ADOB
-
- swms - Variable in class moa.classifiers.meta.BOLE
-
- swms - Variable in class moa.classifiers.meta.OzaBoost
-
- swms - Variable in class moa.classifiers.meta.OzaBoostAdwin
-