Table — NodePit

There are 2896 nodes that can be used as successor for a node with an output port of type

DecisionTable (3.7)

Class for building and using a simple decision table majority classifier. For more information see: Ron Kohavi: The Power of Decision Tables

FURIA (3.7)

FURIA: Fuzzy Unordered Rule Induction Algorithm Details please see: Jens Christian Huehn, Eyke Huellermeier (2009)

JRip (3.7)

This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was proposed by William W

LAC (3.7)

Implements the LAC (Lazy Associative Classifier) algorithm, which uses associative rules to execute classifications

M5Rules (3.7)

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

NNge (3.7)

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

OLM (3.7)

This class is an implementation of the Ordinal Learning Method (OLM). Further information regarding the algorithm and variants can be found in: Arie […]

OneR (3.7)

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

PART (3.7)

Class for generating a PART decision list

Prism (3.7)

Class for building and using a PRISM rule set for classification

Node Connectivity