Communications Session 1B Learning and Discovery Systems

Foundations of Intelligent Systems

Volume 1079 of the series Lecture Notes in Computer Science pp 118-127

Date:

Induction of classification rules from imperfect data

  • Ning ShanAffiliated withDepartment of Computer Science, University of Regina
  • , Howard J. HamiltonAffiliated withDepartment of Computer Science, University of Regina
  • , Nick CerconeAffiliated withDepartment of Computer Science, University of Regina

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Abstract

We present a method for inducing classification rules from imperfect data using an extended version of the rough set model. The salient feature of our method is that it makes use of the statistical information inherent in the information system. Our framework describes the overall induction task in terms of two key subtasks: approximate classification and rule generation.