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Attributes Reduction Using Fuzzy Rough Sets

delete2008-10-01
delete272
PRE
AI
E
Eric C.C. Tsang *
D
Degang Chen
Y
Yeung, Daniel S.
王曦照 cover
王曦照 (Xizhao Wang)
J
J. Lee
DOI:10.1109/TFUZZ.2006.889960delete
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Abstract

Abstract

En 中文
Fuzzy rough sets are the generalization of traditional rough sets to deal with both fuzziness and vagueness in data. The existing researches on fuzzy rough sets are mainly concentrated on the construction of approximation operators. Less effort has been put on the attributes reduction of databases with fuzzy rough sets. This paper mainly focuses on the attributes reduction with fuzzy rough sets. After analyzing the previous works on attributes reduction with fuzzy rough sets, we introduce formal concepts of attributes reduction with fuzzy rough sets and completely study the structure of attributes reduction. An algorithm using discernibility matrix to compute all the attributes reductions is developed. Based on these lines of thought, we set up a solid mathematical foundation for attributes reduction with fuzzy rough sets. The experimental results show that the idea in this paper is feasible and valid.
Keywords:
Attributes reduction
fuzzy rough sets
rough sets

Journal

IEEE Transactions on Fuzzy Systems cover
IEEE Transactions on Fuzzy Systems
IF:
11.9
Papers:
5.0K
Citations:
2.9W

Organization

H
hong kong polytechnic university
Scholars:
3.0W
Papers: 4.1W
Citations: 921
H
Hebei University
Scholars:
1.5W
Papers: 7.8K
Citations: 1.0W
N
north china electric power university
Scholars:
2.5W
Papers: 1.7W
Citations: 16
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Cited Papers

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