There are 2881 nodes that can be used as successor
for a node with an output port of type Table.
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.
Generates an unpruned or pruned C4.5 decision tree (WEKA).
Class for generating an alternating decision tree.
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.
Fast decision tree learner.