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Reference TypeConference Paper (Conference Proceedings)
Last Update2012:
Metadata Last Update2020: administrator
Citation KeyNakamuraPeCoRoPaYa:2012:BiBaAl
TitleBBA: A Binary Bat Algorithm for Feature Selection
FormatDVD, On-line.
Access Date2021, Jan. 27
Number of Files1
Size166 KiB
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Author1 Nakamura, Rodrigo Yuji Mizobe
2 Pereira, Luis Augusto Martins
3 Costa, Kelton Augusto Pontara da
4 Rodrigues, Douglas
5 Papa, Joao Paulo
6 Yang, Xin-She
Affiliation1 Sao Paulo State University - UNESP
2 Sao Paulo State University - UNESP
3 Sao Paulo State University - UNESP
4 Sao Paulo State University - UNESP
5 Sao Paulo State University - UNESP
6 National Physical Laboratory
EditorFreitas, Carla Maria Dal Sasso
Sarkar, Sudeep
Scopigno, Roberto
Silva, Luciano
Conference NameConference on Graphics, Patterns and Images, 25 (SIBGRAPI)
Conference LocationOuro Preto
DateAug. 22-25, 2012
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Tertiary TypeFull Paper
History2012-09-20 16:45:34 :: -> administrator :: 2012
2020-02-19 02:18:28 :: administrator -> :: 2012
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Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
Keywordsfeature selection, bat algorithm, optimum-path forest.
AbstractFeature 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.
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