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## Package weka.classifiers.rules

Class Summary
ConjunctiveRule | This class implements a single conjunctive rule learner that can predict for numeric and nominal class labels. A rule consists of antecedents "AND"ed together and the consequent (class value) for the classification/regression.
DecisionTable | Class for building and using a simple decision table majority classifier. For more information see: Ron Kohavi: The Power of Decision Tables.
DecisionTableHashKey | Class providing hash table keys for DecisionTable
DTNB | Class for building and using a decision table/naive bayes hybrid classifier.
JRip | This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was proposed by William W.
M5Rules | Generates a decision list for regression problems using separate-and-conquer.
NNge | Nearest-neighbor-like algorithm using non-nested generalized exemplars (which are hyperrectangles that can be viewed as if-then rules).
OneR | Class for building and using a 1R classifier; in other words, uses the minimum-error attribute for prediction, discretizing numeric attributes.
PART | Class for generating a PART decision list.
Prism | Class for building and using a PRISM rule set for classification.
Ridor | An implementation of a RIpple-DOwn Rule learner. It generates a default rule first and then the exceptions for the default rule with the least (weighted) error rate.
Rule | Abstract class of generic rule
RuleStats | 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.
ZeroR | Class for building and using a 0-R classifier.

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