# Package weka.classifiers.trees

package weka.classifiers.trees

Related Packages
Package
Description
weka.classifiers
weka.classifiers.trees.adtree
weka.classifiers.trees.ft
weka.classifiers.trees.j48
weka.classifiers.trees.lmt
weka.classifiers.trees.m5
Classes
Class
Description
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.