Attributes reduction based on important degree of attributes in incomplete information system

  • Authors:

  • Jilin Yang;Dongmei Wei;Qiong Liu;Yufeng Hai

  • Affiliations:

  • School of Mathematics, Southwest Jiaotong university, Chengdu, Sichuan, China;School of Mathematics & Computer Science, Xihua University, Chengdu, Sichuan, China;School of Mathematics & Computer Science, Xihua University, Chengdu, Sichuan, China;School of Mathematics & Computer Science, Xihua University, Chengdu, Sichuan, China

  • Venue:
  • FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
  • Year:
  • 2009

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Abstract

In incomplete information systems, based on similarity relation, a method of attributes reduction is discussed in this paper. Relative important degree of attributes is defined. Important degree of attributes is obtained by using the OWA operator to aggregate relative important degree of attributes. Due to finding attributes reduction in accordance with the reorder of attributes which identified by important degree of attributes, the advantage of our method is to reduce the search space of attribute reduction and avoid blindness. Finally, the specific example shows our method is effective.