A fast approach to attribute reduction in incomplete decision systems with tolerance relation-based rough sets

  • Authors:

  • Zuqiang Meng;Zhongzhi Shi

  • Affiliations:

  • The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China and College of Computer, Electronics and Information ...;The Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2009

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Abstract

Efficient attribute reduction in large, incomplete decision systems is a challenging problem; existing approaches have time complexities no less than O(|C|^2|U|^2). This paper derives some important properties of incomplete information systems, then constructs a positive region-based algorithm to solve the attribute reduction problem with a time complexity no more than O(|C|^2|U|log|U|). Furthermore, our approach does not change the size of the original incomplete system. Numerical experiments show that the proposed approach is indeed efficient, and therefore of practical value to many real-world problems. The proposed algorithm can be applied to both consistent and inconsistent incomplete decision systems.