Attribute reduction based on generalized fuzzy evidence theory in fuzzy decision systems

  • Authors:

  • Yan-Qing Yao;Ju-Sheng Mi;Zhou-Jun Li

  • Affiliations:

  • State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China and School of Computer Science and Engineering, Beihang University, Beijing 100191, China;College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang, Hebei 050016, China;State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China and School of Computer Science and Engineering, Beihang University, Beijing 100191, China and Be ...

  • Venue:
  • Fuzzy Sets and Systems
  • Year:
  • 2011

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Abstract

Attribute reduction is viewed as an important issue in data mining and knowledge representation. This paper studies attribute reduction in fuzzy decision systems based on generalized fuzzy evidence theory. The definitions of several kinds of attribute reducts are introduced. The relationships among these reducts are then investigated. In a fuzzy decision system, it is proved that the concepts of fuzzy positive region reduct, lower approximation reduct and generalized fuzzy belief reduct are all equivalent, the concepts of fuzzy upper approximation reduct and generalized fuzzy plausibility reduct are equivalent, and a generalized fuzzy plausibility consistent set must be a generalized fuzzy belief consistent set. In a consistent fuzzy decision system, an attribute set is a generalized fuzzy belief reduct if and only if it is a generalized fuzzy plausibility reduct. But in an inconsistent fuzzy decision system, a generalized fuzzy belief reduct is not a generalized fuzzy plausibility reduct in general.