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Attribute Reduction of Fuzzy Rough Sets Based on Variable Similar Degree |
ZHANG Hui-Zhe, WANG Jian, MEI Hong-Biao |
CIMS Research Center, Tongji University, Shanghai 201804 |
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Abstract A fuzzy rough model based on variable similar degree is presented. It introduces the fuzzy similar degree and extends classical Pawlak's model. Firstly, the definitions of fuzzy similarity matrix and fuzzy difference degree matrix are given. Then, in the light of these definitions, the concepts of knowledge reduction are provided, such as attribute reduction, core, and algorithm of attribute reduction. Moreover, the relation between minimum reduction and core is proved. The proposed method obtains attribute reduction sets at different levels. Meanwhile, it keeps the classification accuracy with better flexibility by adjusting the similar precision. Compared to compact computational domain of fuzzy rough set, the proposed method has better classification accuracy and it provides a new idea for continued attribute data reduction.
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Received: 14 January 2008
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