# 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.
  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.
  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.