Title :
Scatter Search for Rough Set Attribute Reduction
Author :
Wang, Jue ; Hedar, Abdel-Rahman ; Wang, Shouyang
Author_Institution :
Acad. of Math. & Syst. Sci., Chinese Acad. of Sci., Beijing
Abstract :
Attribute reduction of an information system is a key problem in rough set theory and its applications. Using computational intelligence (CI) tools to solve such problems has recently fascinated many researchers. In this paper, we consider a meta-heuristic of scatter search to solve the attribute reduction problem in rough set theory. The proposed method, called scatter search attribute reduction (SSAR), shows promising and competitive performance compared with some other CI tools in terms of solution qualities. Moreover, SSAR shows a superior performance in saving the computational costs.
Keywords :
data reduction; rough set theory; search problems; computational intelligence tool; information system; meta heuristic; rough set attribute reduction; scatter search; Computational efficiency; Computational intelligence; Data mining; Information systems; Machine learning; Pattern recognition; Physics; Rough sets; Scattering; Set theory;
Conference_Titel :
Bio-Inspired Computing: Theories and Applications, 2007. BIC-TA 2007. Second International Conference on
Conference_Location :
Zhengzhou
Print_ISBN :
978-1-4244-4105-1
Electronic_ISBN :
978-1-4244-4106-8
DOI :
10.1109/BICTA.2007.4806458
