MERBIS - A Multi-Objective Evolutionary Rule Base Induction System

نویسندگان

  • Christian Setzkorn
  • Ray C. Paton
چکیده

Classifier induction is a specific data-mining task that is part of the knowledge discovery process. Its objectives are to extract accurate, comprehensible and interesting knowledge. However, most classifier induction approaches focus only on one of these objectives. This paper introduces a Multi-Objective Evolutionary Rule Base Induction System (MERBIS) that is capable of optimising both, accuracy and comprehensibility objectives at the same time. We investigate different parameter sets for this approach and validate its performance on several benchmark data sets.

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تاریخ انتشار 2003