# Package weka.classifiers

package weka.classifiers

Related Packages
Package
Description
weka.classifiers.bayes
weka.classifiers.evaluation
weka.classifiers.functions
weka.classifiers.lazy
weka.classifiers.meta
weka.classifiers.mi
weka.classifiers.misc
weka.classifiers.rules
weka.classifiers.trees
weka.classifiers.xml
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.
IntervalEstimator
Interface for classifiers that can output confidence intervals
IteratedSingleClassifierEnhancer
Abstract utility class for handling settings common to meta classifiers that build an ensemble from a single base learner.
IterativeClassifier
Interface for classifiers that can induce models of growing complexity one step at a time.
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.
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.