Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/25028
Title: A novel algorithm for finding reducts with fuzzy rough sets
Authors: Chen, D
Zhang, L 
Zhao, S
Hu, Q
Zhu, P
Keywords: Attribute reduction
discernibility matrix
fuzzy rough set
minimal element
Issue Date: 2012
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on fuzzy systems, 2012, v. 20, no. 2, 6095617, p. 385-389 How to cite?
Journal: IEEE transactions on fuzzy systems 
Abstract: Attribute reduction is one of the most meaningful research topics in the existing fuzzy rough sets, and the approach of discernibility matrix is the mathematical foundation of computing reducts. When computing reducts with discernibility matrix, we find that only the minimal elements in a discernibility matrix are sufficient and necessary. This fact motivates our idea in this paper to develop a novel algorithm to find reducts that are based on the minimal elements in the discernibility matrix. Relative discernibility relations of conditional attributes are defined and minimal elements in the fuzzy discernibility matrix are characterized by the relative discernibility relations. Then, the algorithms to compute minimal elements and reducts are developed in the framework of fuzzy rough sets. Experimental comparison shows that the proposed algorithms are effective.
URI: http://hdl.handle.net/10397/25028
ISSN: 1063-6706
EISSN: 1941-0034
DOI: 10.1109/TFUZZ.2011.2173695
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