Rough set and scatter search metaheuristic based feature selection for credit scoring
Expert Systems with Applications: An International Journal
Intelligent water drops algorithm for rough set feature selection
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Investigating memetic algorithm in solving rough set attribute reduction
International Journal of Computer Applications in Technology
An Exponential Monte-Carlo algorithm for feature selection problems
Computers and Industrial Engineering
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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.