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http://dx.doi.org/10.5391/JKIIS.2006.16.4.466

Genetic Algorithm Based Feature Selection Method Development for Pattern Recognition  

Park Chang-Hyun (중앙대학교 전자전기공학부)
Kim Ho-Duck (중앙대학교 전자전기공학부)
Yang Hyun-Chang (중앙대학교 전자전기공학부)
Sim Kwee-Bo (중앙대학교 전자전기공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.16, no.4, 2006 , pp. 466-471 More about this Journal
Abstract
IAn important problem of pattern recognition is to extract or select feature set, which is included in the pre-processing stage. In order to extract feature set, Principal component analysis has been usually used and SFS(Sequential Forward Selection) and SBS(Sequential Backward Selection) have been used as a feature selection method. This paper applies genetic algorithm which is a popular method for nonlinear optimization problem to the feature selection problem. So, we call it Genetic Algorithm Feature Selection(GAFS) and this algorithm is compared to other methods in the performance aspect.
Keywords
Feature Selection; Feature extraction; Genetic Algorithm; SFS; Pattern Recognition;
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