DocumentCode :
3109620
Title :
Discernibility Matrix Based Algorithm for Reduction of Attributes
Author :
Wang, Ruizhi ; Miao, Duoqian ; Hu, Guirong
Author_Institution :
Dept. of Comput. Sci. & Technol.,, Tongji Univ., Shanghai
fYear :
2006
fDate :
Dec. 2006
Firstpage :
477
Lastpage :
480
Abstract :
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
Keywords :
computational complexity; decision tables; information systems; rough set theory; NP-complete problem; decision tables; discernibility matrix; information systems; minimal reduct algorithm; rough set theory; Algorithm design and analysis; Computer science; Databases; Heuristic algorithms; Information systems; Intelligent agent; NP-complete problem; Set theory; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology Workshops, 2006. WI-IAT 2006 Workshops. 2006 IEEE/WIC/ACM International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2749-3
Type :
conf
DOI :
10.1109/WI-IATW.2006.58
Filename :
4053296
Link To Document :
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