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%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2012/07.12.18.44
%2 sid.inpe.br/sibgrapi/2012/07.12.18.44.07
%T BBA: A Binary Bat Algorithm for Feature Selection
%D 2012
%A Nakamura, Rodrigo Yuji Mizobe,
%A Pereira, Luis Augusto Martins,
%A Costa, Kelton Augusto Pontara da,
%A Rodrigues, Douglas,
%A Papa, Joao Paulo,
%A Yang, Xin-She,
%@affiliation Sao Paulo State University - UNESP
%@affiliation Sao Paulo State University - UNESP
%@affiliation Sao Paulo State University - UNESP
%@affiliation Sao Paulo State University - UNESP
%@affiliation Sao Paulo State University - UNESP
%@affiliation National Physical Laboratory
%E Freitas, Carla Maria Dal Sasso,
%E Sarkar, Sudeep,
%E Scopigno, Roberto,
%E Silva, Luciano,
%B Conference on Graphics, Patterns and Images, 25 (SIBGRAPI)
%C Ouro Preto
%8 Aug. 22-25, 2012
%S Proceedings
%I IEEE Computer Society
%J Los Alamitos
%K feature selection, bat algorithm, optimum-path forest.
%X 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 bats behavior, which has never been applied to this context so far. The wrapper approach combines the power of exploration of the bats 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 five public datasets have demonstrated that the proposed approach can outperform some well-known swarm-based techniques.
%@language en
%3 updated_paper.pdf


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