DocumentCode :
1898763
Title :
An Approximate Attribute Reduction of Rough Set and Its Algorithm
Author :
Jin-Biao, Shen ; Yue-jin, Lv ; Duo-Xiu, Tao
Author_Institution :
Sch. of Math. & Inf. Sci., Guangxi Univ., Nanning, China
Volume :
2
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
591
Lastpage :
594
Abstract :
In view of the deficiencies of attribute reduction in classic rough set, On condition that knowledge classification ability remains basically unchanged, this paper renders a new definition of the approximate attribute reduction of rough set and discuss its nature and algorithms. Theory proves that approximate attribute reduction is an extension of the traditional attribute reduction. Finally, a concrete example demonstrates the feasibility and effectiveness of approximate attribute reduction dealing with ambiguity and uncertainty of knowledge in information systems.
Keywords :
approximation theory; pattern classification; rough set theory; approximate attribute reduction; information systems; knowledge classification ability; rough set; Automation; Concrete; Helium; Information science; Information systems; Mathematics; Rough sets; Set theory; Sufficient conditions; Uncertainty; approximate attribute reduction; reduction algorithm; rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation, 2009. ICICTA '09. Second International Conference on
Conference_Location :
Changsha, Hunan
Print_ISBN :
978-0-7695-3804-4
Type :
conf
DOI :
10.1109/ICICTA.2009.377
Filename :
5287751
Link To Document :
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