Investigating the Effect of Fixing the Subset Length Using Ant Colony Optimization Algorithms for Feature Subset Selection Problems

The issue of studying the effect of fixing the length of the selected feature subsets using ant colony optimization (ACO) has not yet been studied. This paper addresses this concern by demonstrating four points that are: 1) determining the optimal feature subset, 2) determining the length of the subsets in ACO for subset selection problems, 3) different stopping criteria when solving feature selection by ACO, and 4) experiments on an ACO algorithm for feature selection problems using artificial and real-world datasets in two cases fixing and not fixing the length of the selected feature subsets with the use of a support vector machine (SVM) classifier. The results showed that not fixing the length of the selected feature subsets is better than fixing the length of the selected feature subsets in terms of the classifier accuracy in seven datasets out of ten.