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Discernibility Matrix Based Algorithm for Reduction of Attributes
Hong Kong, China December 18-December 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WI-IATW.2006.582006 IEEE/WIC/ACM International Confe ...
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Ruizhi Wang, Tongji University, China
Duoqian Miao, Tongji University, China
Guirong Hu, Tongji University, China
In rough set theory, it has been proved that finding the minimal reduct of information systems or decision tables is a NP-complete problem. Therefore, it is hard to obtain the set of the most concise rules by existing algorithms for reduction of knowledge. In this paper, the method of finding sub-optimal reduct based on discernibility matrix is proposed. In general, our method is better than existing methods with respect to the minimal reduct. However, we find that existing minimal reduct searching algorithms are incomplete for reduction of attributes in information systems or decision tables. Through analysis, we present a conjecture about the completeness of the minimal reduct algorithm.
Citation:
Ruizhi Wang, Duoqian Miao, Guirong Hu, "Discernibility Matrix Based Algorithm for Reduction of Attributes," wi-iatw, pp.477-480, 2006 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops, 2006
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