2007•Unpublished venueRequires access

Fuzzy-Rough Data Reduction Based on Information Entropy

Junyang Zhao, Zhili Zhang

Abstract

Presently, many researches have been carried out on rough set based data reduction. However, this method encounters a problem when dealing with real-valued data and fuzzy information. By lucubrating the theory of fuzzy rough set and utilizing the definition of information entropy presented in literature [5], the information entropy model of fuzzy rough set has been constructed. Then the conditional information entropy of attributes is adopted to measure the significance of attributes. On this condition, a heuristic fuzzy-rough data reduction method based on information entropy (E-FRDR) has been put forward. Finally, the method is validated by an example that indicates the method is feasible.

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Available abstract

Key concepts: Rough set, Data mining, Entropy (arrow of time), Fuzzy set, Conditional entropy, Fuzzy logic, Computer science, Mathematics