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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPBW34M/3C9ES5P
Repositorysid.inpe.br/sibgrapi/2012/07.12.18.44
Last Update2012:07.31.18.39.56 papa.joaopaulo@gmail.com
Metadatasid.inpe.br/sibgrapi/2012/07.12.18.44.07
Metadata Last Update2020:02.19.02.18.28 administrator
Citation KeyNakamuraPeCoRoPaYa:2012:BiBaAl
TitleBBA: A Binary Bat Algorithm for Feature Selection
FormatDVD, On-line.
Year2012
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
e-Mail Addresspapa.joaopaulo@gmail.com
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 :: papa.joaopaulo@gmail.com -> 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
Transferable1
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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data URLhttp://urlib.net/rep/8JMKD3MGPBW34M/3C9ES5P
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3C9ES5P
Languageen
Target Fileupdated_paper.pdf
User Grouppapa.joaopaulo@gmail.com
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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Empty Fieldsaccessionnumber archivingpolicy archivist area callnumber copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi edition electronicmailaddress group holdercode isbn issn label lineage mark nextedition nexthigherunit notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume

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