Knowledge reduction of rough set based on partition

  • Authors:

  • Xiaobing Pei;Yuanzhen Wang

  • Affiliations:

  • Department of computer science, HuaZhong University of Science & Technology, Wuhan, Hubei, China;Department of computer science, HuaZhong University of Science & Technology, Wuhan, Hubei, China

  • Venue:
  • IDEAL'05 Proceedings of the 6th international conference on Intelligent Data Engineering and Automated Learning
  • Year:
  • 2005

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Abstract

Knowledge reduction is one of the basic contents in rough set theory and one of the most problem in knowledge acquisition. The main objective of this paper is to introduce a new concept of knowledge reduction based on partition. It is referred to as partition reduction. The partition reduction is to unify the definitions of classical knowledge reductions. Classical knowledge reductions such as absolute attribute reduction, relative reduction, distribution reduction, assignment reduction and maximum distribution reduction are special cases of partition reduction. We can establish new types of knowledge reduction to meet our requirements based on partition reduction.