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## Package weka.classifiers.trees

Class Summary
ADTree | Class for generating an alternating decision tree.
BFTree | Class for building a best-first decision tree classifier.
DecisionStump | Class for building and using a decision stump.
FT | Classifier for building 'Functional trees', which are classification trees that could have logistic regression functions at the inner nodes and/or leaves.
Id3 | Class for constructing an unpruned decision tree based on the ID3 algorithm.
J48 | Class for generating a pruned or unpruned C4.5 decision tree.
J48graft | Class for generating a grafted (pruned or unpruned) C4.5 decision tree.
LADTree | Class for generating a multi-class alternating decision tree using the LogitBoost strategy.
LMT | Classifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves.
M5P | M5Base.
NBTree | Class for generating a decision tree with naive Bayes classifiers at the leaves. For more information, see Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid.
RandomForest | Class for constructing a forest of random trees. For more information see: Leo Breiman (2001).
RandomTree | Class for constructing a tree that considers K randomly chosen attributes at each node.
REPTree | Fast decision tree learner.
SimpleCart | Class implementing minimal cost-complexity pruning. Note when dealing with missing values, use "fractional instances" method instead of surrogate split method. For more information, see: Leo Breiman, Jerome H.
UserClassifier | Interactively classify through visual means.

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