DocumentCode :
3292035
Title :
Function S-Rough Sets Method in Feature Selection
Author :
Hu, Haiqing ; Wang, Pitao ; Shi, Kaiquan
Author_Institution :
Sch. of Control Sci. & Eng., Univ. of Jinan, Jinan
Volume :
5
fYear :
2008
fDate :
18-20 Oct. 2008
Firstpage :
261
Lastpage :
265
Abstract :
Function S-rough sets is defined by function equivalence class, function is a kind of feature. By using of function S-rough sets, this paper gives a new feature selection method, gives concepts of lower approximation features and upper approximation features, furthermore, it presents the structure of F-feature pair, gives its characteristic discussion. F-feature selection method given in this paper has gotten applied in image processing, object recognition and etc, it is becoming a new research direction in recognition theory.
Keywords :
approximation theory; feature extraction; rough set theory; F-lower approximation features; F-upper approximation features; R-function equivalence class; feature selection; feature selection method; function S-rough sets method; image processing; object recognition; Control systems; Delay; Fuzzy systems; Image processing; Image recognition; Knowledge engineering; Mathematics; Object recognition; Rough sets; Set theory; eigenvector; feature; feature selection; function S-rough sets; precision;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Jinan Shandong
Print_ISBN :
978-0-7695-3305-6
Type :
conf
DOI :
10.1109/FSKD.2008.204
Filename :
4666534
Link To Document :
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