Genetic Algorithm Based Feature Selection Method Development for Pattern Recognition
Ho-Duck Kim, Chang-Hyun Park, Hyun-Chang Yang, Kwee-Bo Sim · 2006 SICE-ICASE International Joint Conference · 2006
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