This class implements a single conjunctive rule learner* that can predict for numeric and nominal class labels. A rule consists o…

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

Class for building and using a decision table/naive bayes hybrid classifier. At each point in the search, the algorithm evaluates…

This class implements a propositional rule learner*, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was …

Generates a decision list for regression problems using separate-and-conquer. In each iteration it builds a model tree using M5 a…

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

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

Class for generating a PART decision list. Uses separate-and-conquer. Builds a partial C4.5 decision tree in each iteration and m…

Class for building and using a PRISM rule set for classification. Can only deal with nominal attributes. Can't deal with missing …

An implementation of a RIpple-DOwn rule learner*. It generates a default rule first and then the exceptions for the default rule …

Class for building and using a 0-R classifier. Predicts the mean (for a numeric class) or the mode (for a nominal class). (based …