Package weka.classifiers.trees.j48

Class Summary

Class	Description
BinC45ModelSelection	Class for selecting a C4.5-like binary (!) split for a given dataset.
BinC45Split	Class implementing a binary C4.5-like split on an attribute.
C45ModelSelection	Class for selecting a C4.5-type split for a given dataset.
C45PruneableClassifierTree	Class for handling a tree structure that can be pruned using C4.5 procedures.
C45PruneableClassifierTreeG	Class for handling a tree structure that can be pruned using C4.5 procedures and have nodes grafted on.
C45Split	Class implementing a C4.5-type split on an attribute.
ClassifierSplitModel	Abstract class for classification models that can be used recursively to split the data.
ClassifierTree	Class for handling a tree structure used for classification.
Distribution	Class for handling a distribution of class values.
EntropyBasedSplitCrit	"Abstract" class for computing splitting criteria based on the entropy of a class distribution.
EntropySplitCrit	Class for computing the entropy for a given distribution.
GainRatioSplitCrit	Class for computing the gain ratio for a given distribution.
GraftSplit	Class implementing a split for nodes added to a tree during grafting.
InfoGainSplitCrit	Class for computing the information gain for a given distribution.
ModelSelection	Abstract class for model selection criteria.
NBTreeClassifierTree	Class for handling a naive bayes tree structure used for classification.
NBTreeModelSelection	Class for selecting a NB tree split.
NBTreeNoSplit	Class implementing a "no-split"-split (leaf node) for naive bayes trees.
NBTreeSplit	Class implementing a NBTree split on an attribute.
NoSplit	Class implementing a "no-split"-split.
PruneableClassifierTree	Class for handling a tree structure that can be pruned using a pruning set.
SplitCriterion	Abstract class for computing splitting criteria with respect to distributions of class values.
Stats	Class implementing a statistical routine needed by J48 to compute its error estimate.