|
Class Summary |
| AbstractCriterion |
This criterion class can be used to incrementally calculate a benefit. |
| AccuracyCriterion |
Calculates the accuracy benefit. |
| BestRuleInduction |
This operator returns the best rule regarding WRAcc using exhaustive search. |
| BestRuleInduction.RuleWithScoreUpperBound |
Helper class containing a rule and an upper bound for the score. |
| ConjunctiveRuleModel |
Each object of this class represents a conjunctive rule with boolean target
and nominal attributes. |
| InfoGainCriterion |
The info gain criterion for rule learning. |
| NumericalSplitter |
Find the best split point for numerical attributes according to accuracy. |
| Rule |
This class combines several SplitConditions to one rule by conjunctions. |
| RuleLearner |
This operator works similar to the propositional rule learner named
Repeated Incremental Pruning to Produce Error Reduction (RIPPER, Cohen 1995). |
| RuleModel |
The basic rule model. |
| SimpleRuleLearner |
This operator builds an unpruned rule set of classification rules. |
| SingleRuleLearner |
This operator concentrates on one single attribute and determines the best splitting terms
for minimizing the training error. |
| Split |
Contains all information about a numerical split point. |
| TermDetermination |
Determines the best term for the given example set with respect to the criterion. |