Analysis of Problem Spaces and Algorithm Behaviors for Feature Selection
Jin-Seon Lee, Il-Seok Oh · Jeongbo gwahaghoe nonmunji. so'peuteuweeo mich eung'yong · 2006
The feature selection algorithms should broadly and efficiently explore the huge problem spaces to find a good solution. This paper attempts to gain insights on the fitness landscape of the spaces and to improve search capability of the algorithms. We investigate the solution spaces in terms of statistics on local maxima and minima. We also analyze behaviors of the existing algorithms and improve their solutions.