weka.classifiers

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## Package weka.classifiers

Interface Summary
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
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.
EnsembleLibrary | This class represents a library of classifiers.
EnsembleLibraryModel | This class is a light wrapper that is meant to represent a classifier in a classifier library.
EnsembleLibraryModelComparator | This class is a Comparator for the LibraryModel class.
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.
JythonClassifier | A wrapper class for Jython code.
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.

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