||Class for building and using a simple decision table majority classifier.
For more information see:
Ron Kohavi: The Power of Decision Tables.
||Class providing hash table keys for DecisionTable
||This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was proposed by William W.
||Generates a decision list for regression problems using separate-and-conquer.
||Class for building and using a 1R classifier; in other words, uses the minimum-error attribute for prediction, discretizing numeric attributes.
||Class for generating a PART decision list.
||Abstract class of generic rule
||This class implements the statistics functions used in the
propositional rule learner, from the simpler ones like count of
true/false positive/negatives, filter data based on the ruleset, etc.
||Class for building and using a 0-R classifier.