A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest

Rodrigues, Douglas, Pereira, Luís A. M., Nakamura, Rodrigo Y. M., Costa, Kelton A. P., Yang, Xin-She ORCID logoORCID: https://orcid.org/0000-0001-8231-5556, Souza, André N. and Papa, João Paulo (2014) A wrapper approach for feature selection based on Bat Algorithm and Optimum-Path Forest. Expert Systems with Applications, 41 (5) . pp. 2250-2258. ISSN 0957-4174 [Article] (doi:10.1016/j.eswa.2013.09.023)


Besides optimizing classifier predictive performance and addressing the curse of the dimensionality problem, feature selection techniques support a classification model as simple as possible. In this paper, we present a wrapper feature selection approach based on Bat Algorithm (BA) and Optimum-Path Forest (OPF), in which we model the problem of feature selection as an binary-based optimization technique, guided by BA using the OPF accuracy over a validating set as the fitness function to be maximized. Moreover, we present a methodology to better estimate the quality of the reduced feature set. Experiments conducted over six public datasets demonstrated that the proposed approach provides statistically significant more compact sets and, in some cases, it can indeed improve the classification effectiveness.

Item Type: Article
Additional Information: Available online 26 September 2013
Keywords (uncontrolled): Dimensionality reduction; Swarm intelligence; Bat Algorithm; Optimum-Path Forest
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 15628
Useful Links:
Depositing User: Xin-She Yang
Date Deposited: 30 Apr 2015 13:26
Last Modified: 10 Jun 2019 13:07
URI: https://eprints.mdx.ac.uk/id/eprint/15628

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