Fuzzy-Rough Data Reduction Based on Information Entropy

Author

Zhao, Jun-Yang ; Zhang, Zhi-Li

Author_Institution

Xi´´an Res. Inst. Of Hi-tech Hongqing Town, Xi´´an

Volume

7

fYear

2007

fDate

19-22 Aug. 2007

Firstpage

3708

Lastpage

3712

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.

Keywords

data reduction; entropy; fuzzy set theory; rough set theory; data reduction; fuzzy set theory; information entropy; rough set theory; Algorithm design and analysis; Cities and towns; Cybernetics; Fuzzy set theory; Fuzzy sets; Information analysis; Information entropy; Machine learning; Machine learning algorithms; Set theory; Data reduction; Fuzzy rough set; Information entropy; Significance of attributes;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2007 International Conference on

Conference_Location

Hong Kong

Print_ISBN

978-1-4244-0973-0

Electronic_ISBN

978-1-4244-0973-0

Type

conf

DOI

10.1109/ICMLC.2007.4370792

Filename

4370792