Partitions, Coverings, Reducts and Rule Learning in Rough Set Theory

  • Yiyu Yao
  • Rong Fu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6954)

Abstract

When applying rough set theory to rule learning, one commonly associates equivalence relations or partitions to a complete information table and tolerance relations or coverings to an incomplete table. Such associations are sometimes misleading. We argue that Pawlak three-step approach for data analysis indeed uses both partitions and coverings for a complete information table. A slightly different formulation of Pawlak approach is given based on the notions of attribute reducts of a classification table, attribute reducts of objects and rule reducts. Variations of Pawlak approach are examined.

Keywords

Attribute reduction coverings partitions rule learning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yiyu Yao
    • 1
  • Rong Fu
    • 1
  1. 1.Department of Computer ScienceUniversity of ReginaReginaCanada

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