%0 Journal Article %A Ahmed Al-Ani %D 2008 %J International Journal of Mathematical and Computational Sciences %B World Academy of Science, Engineering and Technology %I Open Science Index 17, 2008 %T Feature Subset Selection Using Ant Colony Optimization %U https://publications.waset.org/pdf/9066 %V 17 %X Feature selection is an important step in many pattern classification problems. It is applied to select a subset of features, from a much larger set, such that the selected subset is sufficient to perform the classification task. Due to its importance, the problem of feature selection has been investigated by many researchers. In this paper, a novel feature subset search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results. %P 322 - 327