Redundant data processing based on rough-fuzzy approach

  • Authors:
  • Huanglin Zeng;Hengyou Lan;Xiaohui Zeng

  • Affiliations:
  • Electronics and Information Engineering Department, Sichuan University of Science & Engineering, Zigong, Sichuan, P.R. China;Department of Mathematics, Sichuan University of Science & Engineering, Zigong, Sichuan, P.R. China;Department of Electronics and Engineering, Chengdu University of Information Technology, Chengdu, Sichuan, P.R. China

  • Venue:
  • RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
  • Year:
  • 2006

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Abstract

In this paper, we will try to use fuzzy approach to deal with either incomplete or imprecise even ill-defined database and to use the concepts of rough sets to define equivalence class encoding input data, and eliminate redundant or insignificant attributes in data sets, and incorporate the significant factor of the input feature corresponding to output pattern classification to constitute a class membership function which enhances a mapping characteristic for each of object in the input space belonging to consequent class in the output space