… ant colony optimization (ACO) algorithm for feature selection (FS), called ACOFS, using a
neural network. A key aspect of this algorithm is the selection of a subset of salient features of …

… Therefore, aimed at the defects of the traditional ant colony optimization algorithms, … feature
selection method based on the ant colony optimization algorithm and the feature set selected …

… On the other hand, unsupervised feature selection is a more … feature selection method
based on ant colony optimization, called UFSACO. The method seeks to find the optimal feature …

… We propose a novel binary coded ant colony algorithm by blending of GA and BACO. … a
feature selection approach based on a modified binary coded ant colony optimization algorithm (…

… proposes a feature selection method for data analysis based on Artificial Bee Colony (ABC) …
have been few works on feature selection. Our work proposes a binary version of the ABC …

… At present there are many methods to deal with text feature selection. To improve … feature
selection algorithm that is based on ant colony optimization. Ant colony optimization algorithm …

… for performing feature selection. By … algorithms have been proposed by researchers. In
this section, a review of ACO-based algorithms is presented that is used for feature selection…

… Ant colony optimization (ACO) is a well-explored meta-heuristic algorithm, among whose
many applications feature selection (FS) is an important one. Most existing versions of ACO are …

… a feature selection algorithm based on ant colony optimization (ACO). For n features, existing
ACO-based feature selection … However, we propose a novel algorithm in which the artificial …

… A major aim of the feature selection algorithms is to select a high-quality feature subset
including those which are relevant and irredundant within a reasonable time. ACO is a multi-…