Uses of Class
weka.classifiers.trees.j48.ClassifierSplitModel
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Uses of ClassifierSplitModel in weka.classifiers.trees.j48
Modifier and TypeClassDescriptionclass
Class implementing a binary C4.5-like split on an attribute.class
Class implementing a C4.5-type split on an attribute.final class
Class implementing a "no-split"-split (leaf node) for naive bayes trees.class
Class implementing a NBTree split on an attribute.final class
Class implementing a "no-split"-split.Modifier and TypeMethodDescriptionClassifierTree.getLocalModel()
final ClassifierSplitModel
BinC45ModelSelection.selectModel
(Instances data) Selects C4.5-type split for the given dataset.final ClassifierSplitModel
BinC45ModelSelection.selectModel
(Instances train, Instances test) Selects C4.5-type split for the given dataset.C45ModelSelection.selectModel
(Instances data) Selects C4.5-type split for the given dataset.final ClassifierSplitModel
C45ModelSelection.selectModel
(Instances train, Instances test) Selects C4.5-type split for the given dataset.abstract ClassifierSplitModel
ModelSelection.selectModel
(Instances data) Selects a model for the given dataset.ModelSelection.selectModel
(Instances train, Instances test) Selects a model for the given train data using the given test datafinal ClassifierSplitModel
NBTreeModelSelection.selectModel
(Instances data) Selects NBTree-type split for the given dataset.final ClassifierSplitModel
NBTreeModelSelection.selectModel
(Instances train, Instances test) Selects NBTree-type split for the given dataset.ModifierConstructorDescriptionDistribution
(Instances source, ClassifierSplitModel modelToUse) Creates a distribution according to given instances and split model. -
Uses of ClassifierSplitModel in weka.classifiers.trees.lmt
Modifier and TypeClassDescriptionclass
Helper class for logistic model trees (weka.classifiers.trees.lmt.LMT) to implement the splitting criterion based on residuals of the LogitBoost algorithm.Modifier and TypeMethodDescriptionfinal ClassifierSplitModel
ResidualModelSelection.selectModel
(Instances train) Method not in usefinal ClassifierSplitModel
ResidualModelSelection.selectModel
(Instances data, double[][] dataZs, double[][] dataWs) Selects split based on residuals for the given dataset.final ClassifierSplitModel
ResidualModelSelection.selectModel
(Instances train, Instances test) Method not in use