Induction of classification rules from imperfect data

  • Ning Shan
  • Howard J. Hamilton
  • Nick Cercone
Communications Session 1B Learning and Discovery Systems
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1079)

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.

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Copyright information

© Springer-Verlag 1996

Authors and Affiliations

  • Ning Shan
    • 1
  • Howard J. Hamilton
    • 1
  • Nick Cercone
    • 1
  1. 1.Department of Computer ScienceUniversity of ReginaReginaCanada

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