Kernel KNN Algorithm based on Simultaneous Feature Selection and Parameter Optimization by PSO
Feature selection and classifier parameter optimization are two important aspects for improving classifier performance and are solved separately traditionally. Recently, with the wide applications of evolutionary computation in pattern recognition area, simultaneous feature selection and parameter optimization became possible and tendency. To solve the problem, we proposed a simultaneous feature selection and parameter optimization algorithm based on binary PSO algorithm. The experiments show that the algorithm can efficiently find the suitable feature subsets and parameters, which result in good classification performance.