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