Package moa.classifiers.multilabel

Class MajorityLabelset

java.lang.Object

moa.AbstractMOAObject

moa.options.AbstractOptionHandler

moa.classifiers.AbstractClassifier

moa.classifiers.AbstractMultiLabelLearner

moa.classifiers.multilabel.MajorityLabelset

All Implemented Interfaces:

Configurable, java.io.Serializable, CapabilitiesHandler, Classifier, MultiLabelLearner, MultiTargetRegressor, AWTRenderable, Learner<Example<Instance>>, MOAObject, OptionHandler

public class MajorityLabelset
extends AbstractMultiLabelLearner
implements MultiTargetRegressor

Majority Labelset classifier. Each labelset combination of relevances, e.g. [0,0,1,1,0,0], is treated as a single class value.

Version:

$Revision: 1 $

Author:

Jesse Read ([email protected])

See Also:

Serialized Form

Field Summary

Fields inherited from class moa.classifiers.AbstractClassifier

classifierRandom, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel

Fields inherited from class moa.options.AbstractOptionHandler

config

Constructor Summary

Constructors

Constructor	Description
MajorityLabelset()

Method Summary

Modifier and Type	Method	Description
void	getModelDescription(java.lang.StringBuilder out, int indent)	Returns a string representation of the model.
protected Measurement[]	getModelMeasurementsImpl()	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.
Prediction	getPredictionForInstance(MultiLabelInstance x)
java.lang.String	getPurposeString()	Dictionary with option texts and objects
boolean	isRandomizable()	Gets whether this learner needs a random seed.
void	resetLearningImpl()	Resets this classifier.
void	trainOnInstanceImpl(MultiLabelInstance x)

Methods inherited from class moa.classifiers.AbstractClassifier

contextIsCompatible, copy, correctlyClassifies, defineImmutableCapabilities, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getModel, getModelContext, getModelMeasurements, getNominalValueString, getSubClassifiers, getSublearners, getVotesForInstance, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, resetLearning, setModelContext, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance, trainOnInstance

Methods inherited from class moa.AbstractMOAObject

copy, measureByteSize, measureByteSize, toString

Methods inherited from class moa.classifiers.AbstractMultiLabelLearner

getPredictionForInstance, getPredictionForInstance, getVotesForInstance, trainOnInstanceImpl

Methods inherited from class moa.options.AbstractOptionHandler

getCLICreationString, getOptions, getPreparedClassOption, prepareClassOptions, prepareForUse, prepareForUse

Methods inherited from interface moa.gui.AWTRenderable

getAWTRenderer

Methods inherited from interface moa.capabilities.CapabilitiesHandler

getCapabilities

Methods inherited from interface moa.classifiers.Classifier

copy, correctlyClassifies, getPredictionForInstance, getSubClassifiers, getVotesForInstance, trainOnInstance

Methods inherited from interface moa.learners.Learner

getModel, getModelContext, getModelMeasurements, getPredictionForInstance, getSublearners, getVotesForInstance, resetLearning, setModelContext, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance

Methods inherited from interface moa.MOAObject

getDescription, measureByteSize

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface moa.options.OptionHandler

getCLICreationString, getOptions, prepareForUse, prepareForUse

Constructor Detail

MajorityLabelset

public MajorityLabelset()

Method Detail

getPurposeString

public java.lang.String getPurposeString()

Description copied from class: AbstractOptionHandler

Dictionary with option texts and objects

Specified by:

getPurposeString in interface OptionHandler

Overrides:

getPurposeString in class AbstractClassifier

Returns:

the string with the purpose of this object

resetLearningImpl

public void resetLearningImpl()

Description copied from class: AbstractClassifier

Resets this classifier. It must be similar to starting a new classifier from scratch.

The reason for ...Impl methods: ease programmer burden by not requiring them to remember calls to super in overridden methods. Note that this will produce compiler errors if not overridden.

Specified by:

resetLearningImpl in class AbstractClassifier

trainOnInstanceImpl

public void trainOnInstanceImpl(MultiLabelInstance x)

Specified by:

trainOnInstanceImpl in interface MultiLabelLearner

Specified by:

trainOnInstanceImpl in class AbstractMultiLabelLearner

getPredictionForInstance

public Prediction getPredictionForInstance(MultiLabelInstance x)

Specified by:

getPredictionForInstance in interface MultiLabelLearner

Specified by:

getPredictionForInstance in class AbstractMultiLabelLearner

getModelMeasurementsImpl

protected Measurement[] getModelMeasurementsImpl()

Description copied from class: 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. Note that this will produce compiler errors if not overridden.

Specified by:

getModelMeasurementsImpl in class AbstractClassifier

Returns:

an array of measurements to be used in evaluation tasks

isRandomizable

public boolean isRandomizable()

Description copied from interface: Learner

Gets whether this learner needs a random seed. Examples of methods that needs a random seed are bagging and boosting.

Specified by:

isRandomizable in interface Learner<Example<Instance>>

Returns:

true if the learner needs a random seed.

getModelDescription

public void getModelDescription(java.lang.StringBuilder out,
                                int indent)

Description copied from class: AbstractClassifier

Returns a string representation of the model.

Specified by:

getModelDescription in class AbstractClassifier

Parameters:

out - the stringbuilder to add the description

indent - the number of characters to indent