IREP++, A Faster Rule Learning Algorithm

نویسندگان

  • Oliver Dain
  • Robert K. Cunningham
  • Stephen Boyer
چکیده

We present IREP++, a rule learning algorithm similar to RIPPER and IREP. Like these other algorithms IREP++ produces accurate, human readable rules from noisy data sets. However IREP++ is able to produce such rule sets more quickly and can often express the target concept with fewer rules and fewer literals per rule resulting in a concept description that is easier for humans to understand. The new algorithm is fast enough for interactive training with very large data sets.

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تاریخ انتشار 2004