Binary Bat Algorithm for Feature Selection

Nenhuma Miniatura disponível




Nakamura, Rodrigo Yuji Mizobe [UNESP]
Pereira, Luís Augusto Martins [UNESP]
Rodrigues, Douglas [UNESP]
Costa, Kelton Augusto Pontara [UNESP]
Papa, João Paulo [UNESP]
Yang, Xin-She

Título da Revista

ISSN da Revista

Título de Volume



Feature selection aims to find the most important information to save computational efforts and data storage. We formulated this task as a combinatorial optimization problem since the exponential growth of possible solutions makes an exhaustive search infeasible. In this work, we propose a new nature-inspired feature selection technique based on bats behavior, namely, binary bat algorithm The wrapper approach combines the power of exploration of the bats together with the speed of the optimum-path forest classifier to find a better data representation. Experiments in public datasets have shown that the proposed technique can indeed improve the effectiveness of the optimum-path forest and outperform some well-known swarm-based techniques. © 2013 Copyright © 2013 Elsevier Inc. All rights reserved.



Bat algorithm, Feature selection, Metaheuristic algorithms, Optimum-path forest classifier, Pattern classification

Como citar

Swarm Intelligence and Bio-Inspired Computation, p. 225-237.