Title :
Genetic Algorithm Based Feature Selection Method Development for Pattern Recognition
Author :
Kim, Ho-Duck ; Park, Chang-Hyun ; Yang, Hyun-Chang ; Sim, Kwee-Bo
Author_Institution :
Dept. of Electr. & Electron. Eng., Chungang Univ., Seoul
Abstract :
An 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 extraction; genetic algorithms; principal component analysis; feature extraction; feature selection method; genetic algorithm; nonlinear optimization problem; pattern recognition; principal component analysis; sequential backward selection; sequential forward selection; Emotion recognition; Feature extraction; Genetic algorithms; Genetic engineering; Genetic programming; Optimization methods; Pattern recognition; Principal component analysis; Search methods; Speech; Feature Selection; Feature extraction; Genetic Algorithm; Pattern Recognition; SFS;
Conference_Titel :
SICE-ICASE, 2006. International Joint Conference
Conference_Location :
Busan
Print_ISBN :
89-950038-4-7
Electronic_ISBN :
89-950038-5-5
DOI :
10.1109/SICE.2006.315742
