A comparative study on binary Artificial Bee Colony optimization methods for feature selection

Zeynep Banu Ozger; Bulent Bolat; Banu Diri

doi:10.1109/INISTA.2016.7571836

A comparative study on binary Artificial Bee Colony optimization methods for feature selection

Zeynep Banu Ozger, Bulent Bolat, Banu Diri

Yildiz Technical University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Citations (Scopus)

Abstract

Feature selection is a major pre-processinş technique which aims to pick out distinctive features from whole dataset. In this way it is intended to reduce computational cost o the classification process. Artificial Bee Colony (ABC) algorithm is an evolutionary based swarm intelligence optimization method In this study, some of the variants of binary ABC algorithms are implemented to the feature selection problem using 10 UC datasets. The results show that ABC algorithm is useful for the area.

Original language	English
Title of host publication	Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016
Editors	Tulay Yuldirim, Mirel Cosulschi, Adina Magda Florea, Costin Badica, Petia Koprinkova-Hristova
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467399104
DOIs	https://doi.org/10.1109/INISTA.2016.7571836
Publication status	Published - 19 Sept 2016
Externally published	Yes
Event	2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016 - Sinaia, Romania Duration: 2 Aug 2016 → 5 Aug 2016

Publication series

Name	Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016

Conference

Conference	2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016
Country/Territory	Romania
City	Sinaia
Period	2/08/16 → 5/08/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

artificial bee colony classification
feature selection

Access to Document

10.1109/INISTA.2016.7571836

Cite this

Ozger, Z. B., Bolat, B., & Diri, B. (2016). A comparative study on binary Artificial Bee Colony optimization methods for feature selection. In T. Yuldirim, M. Cosulschi, A. M. Florea, C. Badica, & P. Koprinkova-Hristova (Eds.), Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016 Article 7571836 (Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INISTA.2016.7571836

Ozger, Zeynep Banu ; Bolat, Bulent ; Diri, Banu. / A comparative study on binary Artificial Bee Colony optimization methods for feature selection. Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016. editor / Tulay Yuldirim ; Mirel Cosulschi ; Adina Magda Florea ; Costin Badica ; Petia Koprinkova-Hristova. Institute of Electrical and Electronics Engineers Inc., 2016. (Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016).

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editor = "Tulay Yuldirim and Mirel Cosulschi and Florea, {Adina Magda} and Costin Badica and Petia Koprinkova-Hristova",

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Ozger, ZB, Bolat, B & Diri, B 2016, A comparative study on binary Artificial Bee Colony optimization methods for feature selection. in T Yuldirim, M Cosulschi, AM Florea, C Badica & P Koprinkova-Hristova (eds), Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016., 7571836, Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016, Institute of Electrical and Electronics Engineers Inc., 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016, Sinaia, Romania, 2/08/16. https://doi.org/10.1109/INISTA.2016.7571836

A comparative study on binary Artificial Bee Colony optimization methods for feature selection. / Ozger, Zeynep Banu; Bolat, Bulent; Diri, Banu.
Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016. ed. / Tulay Yuldirim; Mirel Cosulschi; Adina Magda Florea; Costin Badica; Petia Koprinkova-Hristova. Institute of Electrical and Electronics Engineers Inc., 2016. 7571836 (Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Bolat, Bulent

AU - Diri, Banu

PY - 2016/9/19

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N2 - Feature selection is a major pre-processinş technique which aims to pick out distinctive features from whole dataset. In this way it is intended to reduce computational cost o the classification process. Artificial Bee Colony (ABC) algorithm is an evolutionary based swarm intelligence optimization method In this study, some of the variants of binary ABC algorithms are implemented to the feature selection problem using 10 UC datasets. The results show that ABC algorithm is useful for the area.

AB - Feature selection is a major pre-processinş technique which aims to pick out distinctive features from whole dataset. In this way it is intended to reduce computational cost o the classification process. Artificial Bee Colony (ABC) algorithm is an evolutionary based swarm intelligence optimization method In this study, some of the variants of binary ABC algorithms are implemented to the feature selection problem using 10 UC datasets. The results show that ABC algorithm is useful for the area.

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Ozger ZB, Bolat B, Diri B. A comparative study on binary Artificial Bee Colony optimization methods for feature selection. In Yuldirim T, Cosulschi M, Florea AM, Badica C, Koprinkova-Hristova P, editors, Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016. Institute of Electrical and Electronics Engineers Inc. 2016. 7571836. (Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016). doi: 10.1109/INISTA.2016.7571836

A comparative study on binary Artificial Bee Colony optimization methods for feature selection

Abstract

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Bibliographical note

Keywords

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