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Optimizing Feature Selection through Binary Charged System Search

2013; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-642-40261-6_45

1611-3349

Douglas Rodrigues, Luís A. M. Pereira, João Paulo Papa, Caio C. O. Ramos, André Nunes de Souza, Luciene Patrici Papa,

Face and Expression Recognition

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques.