Fuzzy rough set based attribute reduction for information systems with fuzzy decisions

  • Authors:

  • Qiang He;Congxin Wu;Degang Chen;Suyun Zhao

  • Affiliations:

  • Department of Mathematics, Harbin Institute of Technology, Harbin 150001, PR China;Department of Mathematics, Harbin Institute of Technology, Harbin 150001, PR China;Department of Mathematics and Physics, North China Electric Power University, Beijing 102206, PR China;Department of Mathematics and Computer Science, Hebei University, Baoding 071002, PR China

  • Venue:
  • Knowledge-Based Systems
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Fuzzy rough set is a generalization of crisp rough set to deal with data sets with real value attributes. A primary use of fuzzy rough set theory is to perform attribute reduction for decision systems with numerical conditional attribute values and crisp (symbolic) decision attributes. In this paper we define inconsistent fuzzy decision system and their reductions, and develop discernibility matrix-based algorithms to find reducts. Finally, two heuristic algorithms are developed and comparison study is provided with the existing algorithms of attribute reduction with fuzzy rough sets. The proposed method in this paper can deal with decision systems with numerical conditional attribute values and fuzzy decision attributes rather than crisp ones. Experimental results imply that our algorithm of attribute reduction with general fuzzy rough sets is feasible and valid.