Generic Port — NodePit

There are 5201 nodes that can be used as predessesor for a node with an input port of type

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.

Interactively classify through visual means.

This class implements a single conjunctive rule learner that can predict for numeric and nominal class labels.

Class for building and using a simple decision table majority classifier.

This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER).

Generates a decision list for regression problems using separate-and-conquer.

Nearest-neighbor-like algorithm using non-nested generalized exemplars (which are hyperrectangles that can be viewed as if-then rules).

Class for building and using a 1R classifier; in other words, uses the minimum-error attribute for prediction, discretizing numeric attributes.

Node Connectivity