Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Genetic Algorithm Based Feature Selection Method Development for Pattern Recognition

패턴 인식문제를 위한 유전자 알고리즘 기반 특징 선택 방법 개발

  • 박창현 (중앙대학교 전자전기공학부) ;
  • 김호덕 (중앙대학교 전자전기공학부) ;
  • 양현창 (중앙대학교 전자전기공학부) ;
  • 심귀보 (중앙대학교 전자전기공학부)
  • Published : 2006.08.01
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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.

패턴 인식 문제에서 중요한 전처리 과정 중 하나는 특정을 선택하거나 추출하는 부분이다. 특정을 추출하는 방법으로는 PCA가 보통 사용되고 특정을 선택하는 방법으로는 SFS 나 SBS 등의 방법들이 자주 사용되고 있다. 본 논문은 진화 연산 방법으로써 비선형 최적화 문제에서 유용하게 사용되어 지고 있는 유전자 알고리즘을 특정 선택에 적용하는 유전자 알고리즘 특정 선택 (Genetic Algorithm Feature Selection: GAFS)방법을 개발하여 다른 특징 선택 알고리즘과의 비교를 통해 본 알고리즘의 성능을 관찰한다.

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References

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