Package weka.classifiers

Interface Summary

Interface	Description
IntervalEstimator	Interface for classifiers that can output confidence intervals
IterativeClassifier	Interface for classifiers that can induce models of growing complexity one step at a time.
Sourcable	Interface for classifiers that can be converted to Java source.
UpdateableClassifier	Interface to incremental classification models that can learn using one instance at a time.

Class Summary

Class	Description
BVDecompose	Class for performing a Bias-Variance decomposition on any classifier using the method specified in: Ron Kohavi, David H.
BVDecomposeSegCVSub	This class performs Bias-Variance decomposion on any classifier using the sub-sampled cross-validation procedure as specified in (1). The Kohavi and Wolpert definition of bias and variance is specified in (2). The Webb definition of bias and variance is specified in (3). Geoffrey I.
CheckClassifier	Class for examining the capabilities and finding problems with classifiers.
CheckSource	A simple class for checking the source generated from Classifiers implementing the weka.classifiers.Sourcable interface.
Classifier	Abstract classifier.
CostMatrix	Class for storing and manipulating a misclassification cost matrix.
Evaluation	Class for evaluating machine learning models.
IteratedSingleClassifierEnhancer	Abstract utility class for handling settings common to meta classifiers that build an ensemble from a single base learner.
MultipleClassifiersCombiner	Abstract utility class for handling settings common to meta classifiers that build an ensemble from multiple classifiers.
RandomizableClassifier	Abstract utility class for handling settings common to randomizable classifiers.
RandomizableIteratedSingleClassifierEnhancer	Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.
RandomizableMultipleClassifiersCombiner	Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from multiple classifiers based on a given random number seed.
RandomizableSingleClassifierEnhancer	Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.
SingleClassifierEnhancer	Abstract utility class for handling settings common to meta classifiers that use a single base learner.