A PSO and pattern search based memetic algorithm for SVMs parameters optimization

7 Addressing the issue of SVMs parameters optimization, this study proposes an efficient 8 memetic algorithm based on Particle Swarm Optimization algorithm (PSO) and Pattern Search 9 (PS). In the proposed memetic algorithm, PSO is responsible for exploration of the search space 10 and the detection of the potential regions with optimum solutions, while pattern search (PS) is 11 used to produce an effective exploitation on the potential regions obtained by PSO. Moreover, a 12 novel probabilistic selection strategy is proposed to select the appropriate individuals among the 13 current population to undergo local refinement, keeping a well balance between exploration and 14 exploitation. Experimental results confirm that the local refinement with PS and our proposed 15 selection strategy are effective, and finally demonstrate effectiveness and robustness of the 16 proposed PSO-PS based MA for SVMs parameters optimization. 17 18