This category contains 14 nodes.
Class for generating an alternating decision tree.
Class for building a best-first decision tree classifier.
Class for building and using a decision stump.
Class for constructing an unpruned decision tree based on the ID3 algorithm.
Class for generating an alternating decision tree.
Generates an unpruned or pruned C4.5 decision tree (WEKA).
Classifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves.
M5Base. Implements base routines for generating M5 Model trees and rules.
Class for generating a decision tree with naive Bayes classifiers at the leaves.
Class for constructing a forest of random trees.