A note on genetic algorithms for large-scale feature selection
Pattern Recognition Letters
Floating search methods in feature selection
Pattern Recognition Letters
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
The Ant System Applied to the Quadratic Assignment Problem
IEEE Transactions on Knowledge and Data Engineering
Feature Subset Selection Using a Genetic Algorithm
IEEE Intelligent Systems
Further Research on Feature Selection and Classification Using Genetic Algorithms
Proceedings of the 5th International Conference on Genetic Algorithms
Feature selection from huge feature sets in the context of computer vision
Feature selection from huge feature sets in the context of computer vision
Ant colony optimization theory: a survey
Theoretical Computer Science
An Efficient Face Recognition System Using a New Optimized Localization Method
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Dimensionality reduction using genetic algorithms
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Combined Ant Colony and Differential Evolution Feature Selection Algorithm
ANTS '08 Proceedings of the 6th international conference on Ant Colony Optimization and Swarm Intelligence
A novel hybrid ACO-GA algorithm for text feature selection
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
An Efficient Feature Selection Using Ant Colony Optimization Algorithm
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
An ACO-based algorithm for parameter optimization of support vector machines
Expert Systems with Applications: An International Journal
A new hybrid ant colony optimization algorithm for feature selection
Expert Systems with Applications: An International Journal
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Feature Selection (FS) and reduction of pattern dimensionality is a most important step in pattern recognition systems. One approach in the feature selection area is employing population-based optimization algorithms such as Genetic Algorithm (GA)-based method and Ant Colony Optimization (ACO)- based method. This paper presents a novel feature selection method that is based on Ant Colony Optimization (ACO). ACO algorithm is inspired of ant's social behavior in their search for the shortest paths to food sources. Most common techniques for ACO-Based feature selection use the priori information of features. However, in the proposed algorithm, classifier performance and the length of selected feature vector are adopted as heuristic information for ACO. So, we can select the optimal feature subset without the priori information of features. This approach is easily implemented and because of using one simple classifier in it, its computational complexity is very low. Simulation results on face recognition system and ORL database show the superiority of the proposed algorithm.