@article{(Open Science Index):https://publications.waset.org/pdf/10371, title = {Ant Colony Optimization for Feature Subset Selection}, author = {Ahmed Al-Ani }, country = {}, institution = {}, abstract = {The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that utilizes the ACO algorithm to implement a feature subset search procedure. Initial results obtained using the classification of speech segments are very promising.}, journal = {International Journal of Computer and Information Engineering}, volume = {1}, number = {4}, year = {2007}, pages = {999 - 1002}, ee = {https://publications.waset.org/pdf/10371}, url = {https://publications.waset.org/vol/4}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 4, 2007}, }