Improved Artificial Bee Colony Algorithm and its Application in Classification

Wang, Haiquan; Wei, Jianhua; Wen, Shengjun; Yu, Hongnian; Zhang, Xiguang

Abstract

For improving the classification accuracy of the classifier, a novel classification methodology based on artificial bee colony algorithm is proposed for optimal feature and SVM parameters selection. In order to balance the ability of exploration and exploitation of traditional ABC algorithm, improvements are introduced for the generation of initial solution set and onlooker bee stage. The proposed algorithm is applied to four datasets with different attribute characteristics from UCI and efficiency of the algorithm is proved from the results.

Citation

Wang, H., Wei, J., Wen, S., Yu, H., & Zhang, X. (2018). Improved Artificial Bee Colony Algorithm and its Application in Classification. Journal of Robotics and Mechatronics, 30(6), 921-926. https://doi.org/10.20965/jrm.2018.p0921

• Journal Article Type: Article
• Acceptance Date: Sep 26, 2018
• Online Publication Date: Dec 20, 2018
• Publication Date: Dec 20, 2018
• Deposit Date: Jun 17, 2022
• Journal: Journal of Robotics and Mechatronics
• Print ISSN: 0915-3942
• Electronic ISSN: 0915-3942
• Peer Reviewed: Peer Reviewed
• Volume: 30
• Issue: 6
• Pages: 921-926
• DOI: https://doi.org/10.20965/jrm.2018.p0921
• Keywords: artificial bee colony algorithm, classifier, SVM, UCI database, wrapper method
• Public URL: http://researchrepository.napier.ac.uk/Output/2879959