Package weka.classifiers

Interface Summary

Interface	Description
Classifier	Classifier interface.
ConditionalDensityEstimator	Interface for numeric prediction schemes that can output conditional density estimates.
IntervalEstimator	Interface for numeric prediction schemes that can output prediction 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.
UpdateableBatchProcessor	Updateable classifiers can implement this if they wish to be informed at the end of the training stream.
UpdateableClassifier	Interface to incremental classification models that can learn using one instance at a time.

Class Summary

Class	Description
AbstractClassifier	Abstract classifier.
AggregateableEvaluation	Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.
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.
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.
ParallelIteratedSingleClassifierEnhancer	Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel from a single base learner.
ParallelMultipleClassifiersCombiner	Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using 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.
RandomizableParallelIteratedSingleClassifierEnhancer	Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble in parallel from a single base learner.
RandomizableParallelMultipleClassifiersCombiner	Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using 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.