A Binary classifier based on Firefly Algorithm

This work implements the Firefly algorithm (FA) to find the best decision hyper-plane in the feature space. The proposed classifier uses a cross-validation of a 10-fold portioning for the training and the testing phases used for classification. Five pattern recognition binary benchmark problems with...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Al-Abdallah, Raed Z. (author)
مؤلفون آخرون: Ameera S. Jaradat (author), Abu Doush, Iyad (author), Jaradatm, Yazan (author)
منشور في: 2018
الوصول للمادة أونلاين:http://hdl.handle.net/11675/5025
http://www.jjcit.org/Volume%2003,%20Number%2003/3-DOI%2010.5455-jjcit.71-1501152301.pdf
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author Al-Abdallah, Raed Z.
author2 Ameera S. Jaradat
Abu Doush, Iyad
Jaradatm, Yazan
author2_role author
author
author
author_facet Al-Abdallah, Raed Z.
Ameera S. Jaradat
Abu Doush, Iyad
Jaradatm, Yazan
author_role author
dc.creator.none.fl_str_mv Al-Abdallah, Raed Z.
Ameera S. Jaradat
Abu Doush, Iyad
Jaradatm, Yazan
dc.date.none.fl_str_mv 2018-11-04T10:06:07Z
2018-11-04T10:06:07Z
Dec 2017
dc.identifier.none.fl_str_mv http://hdl.handle.net/11675/5025
http://www.jjcit.org/Volume%2003,%20Number%2003/3-DOI%2010.5455-jjcit.71-1501152301.pdf
dc.publisher.none.fl_str_mv Jordanian Journal of Computers and Information Technology
dc.title.none.fl_str_mv A Binary classifier based on Firefly Algorithm
dc.type.none.fl_str_mv Journal Article
Peer-Reviewed
info:eu-repo/semantics/publishedVersion
description This work implements the Firefly algorithm (FA) to find the best decision hyper-plane in the feature space. The proposed classifier uses a cross-validation of a 10-fold portioning for the training and the testing phases used for classification. Five pattern recognition binary benchmark problems with different feature vector dimensions are used to demonstrate the effectiveness of the proposed classifier. We compare the FA classifier results with those of other approaches through two experiments. The experimental results indicated that FA classifier is a competitive classification technique. The FA shows better results in three out of the four tested datasets used in the second experiment
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oai_identifier_str oai:dspace.auk.edu.kw:11675/5025
publishDate 2018
publisher.none.fl_str_mv Jordanian Journal of Computers and Information Technology
repository.mail.fl_str_mv
repository.name.fl_str_mv
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spelling A Binary classifier based on Firefly AlgorithmAl-Abdallah, Raed Z.Ameera S. JaradatAbu Doush, IyadJaradatm, YazanThis work implements the Firefly algorithm (FA) to find the best decision hyper-plane in the feature space. The proposed classifier uses a cross-validation of a 10-fold portioning for the training and the testing phases used for classification. Five pattern recognition binary benchmark problems with different feature vector dimensions are used to demonstrate the effectiveness of the proposed classifier. We compare the FA classifier results with those of other approaches through two experiments. The experimental results indicated that FA classifier is a competitive classification technique. The FA shows better results in three out of the four tested datasets used in the second experimentJordanian Journal of Computers and Information Technology2018-11-04T10:06:07Z2018-11-04T10:06:07ZDec 2017Journal ArticlePeer-Reviewedinfo:eu-repo/semantics/publishedVersionhttp://hdl.handle.net/11675/5025http://www.jjcit.org/Volume%2003,%20Number%2003/3-DOI%2010.5455-jjcit.71-1501152301.pdfoai:dspace.auk.edu.kw:11675/50252022-01-13T09:22:07Z
spellingShingle A Binary classifier based on Firefly Algorithm
Al-Abdallah, Raed Z.
status_str publishedVersion
title A Binary classifier based on Firefly Algorithm
title_full A Binary classifier based on Firefly Algorithm
title_fullStr A Binary classifier based on Firefly Algorithm
title_full_unstemmed A Binary classifier based on Firefly Algorithm
title_short A Binary classifier based on Firefly Algorithm
title_sort A Binary classifier based on Firefly Algorithm
url http://hdl.handle.net/11675/5025
http://www.jjcit.org/Volume%2003,%20Number%2003/3-DOI%2010.5455-jjcit.71-1501152301.pdf