A Simple, Fast, and Effective Rule Learner

Wedescribe SLIPPER~ a newrule learner that generates rulesets by repeatedly boosting a simple, greedy, rule-builder. Likethe rulesets built byother rule learners, the ensembleof rules created by SLIPPER is compact and comprehensible. This is madepossible by imposingappropriate constraints on the rule-builder, andby use of a recently-proposedgeneralization of Adaboostcalled confidence-ratedboosting. In spite of its relative simplicity, SLIPPER is highly scalable, andan effective learner. Experimentally, SLIPPER scales no worse than O(nlog n), wheren is the numberof examples, and on a set of 32 benchmark problems, SLIPPER achieves lower error rates than RIPPER 20 times, and lowererror rates than C4. 5rules22times.

Authors

• William W. Cohen Google AI
• Yoram Singer
• AT
• T Labs - Research

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