Introduction

This page contains the index for the overview information for all the classification schemes in Weka.

Bayes AODE AODEsr BayesianLogisticRegression BayesNet ComplementNaiveBayes DMNBtext HNB NaiveBayes NaiveBayesMultinomial NaiveBayesMultinomialUpdateable NaiveBayesMultinomialText NaiveBayesSimple NaiveBayesUpdateable WAODE\\\\	Functions FLDA GaussianProcesses IsotonicRegression LeastMedSq LibLINEAR LibSVM LinearRegression Logistic LDA MLPClassifier MLPRegressor MultilayerPerceptron NonNegativeLogisticRegression PaceRegression PLSClassifier QDA RBFNetwork RBFClassifier RBFRegressor SimpleLinearRegression SimpleLogistic SGD SGDText SMO SMOreg SPegasos SVMreg VotedPerceptron Winnow\\\\	Trees ADTree BFTree DecisionStump ExtraTree FT HoeffdingTree Id3 J48 J48graft LADTree LMT M5P NBTree RandomForest RandomTree REPTree SimpleCart UserClassifier\\\\
Lazy IB1 IBk KStar LBR LWL\\\\	Rules ConjunctiveRule DecisionTable DTNB FURIA JRip M5Rules NNge OneR PART Prism Ridor ZeroR\\\\	Meta AdaBoostM1 AdditiveRegression AttributeSelectedClassifier Bagging ClassificationViaClustering ClassificationViaRegression CostSensitiveClassifier CVParameterSelection Dagging Decorate END EnsembleSelection FilteredClassifier Grading GridSearch LogitBoost MetaCost MultiBoostAB MultiClassClassifier MultiClassClassifierUpdateable MultiScheme OneClassClassifier OrdinalClassClassifier RacedIncrementalLogitBoost RandomCommittee RandomSubSpace RealAdaBoost RegressionByDiscretization RotationForest Stacking StackingC ThresholdSelector Vote ClassBalancedND DataNearBalancedND ND\\\\
Multi-instance CitationKNN MDD MIBoost MIDD MIEMDD MILR MINND MIOptimalBall MIRI MISMO MISVM MITI MIWrapper SimpleMI TLD TLDSimple\\\\	Miscellaneous HyperPipes InputMappedClassifier MinMaxExtension OLM OSDL SerializedClassifier VFI\\\\

Pentaho Data Mining

Classifiers

Introduction

Bayes

Functions

Trees

Lazy

Rules

Meta

Multi-instance

Miscellaneous

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