Table — NodePit

There are 2898 nodes that can be used as successor for a node with an output port of type

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.

Class for constructing a forest of random trees.

Class for constructing a tree that considers K randomly chosen attributes at each node.

Class implementing minimal cost-complexity pruning.

Node Connectivity