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To enhance exploitation capacity, a binary learning strategy is proposed to enable each bee to learn from the superior individuals in each dimension. A dynamic Cauchy mutation is introduced to diversify the population distribution. Ten datasets from UCI repository are adopted as test problems, and the average results of cross-validation of BSTABC-DCM are compared with other seven popular swarm intelligence metaheuristics. Experimental results demonstrate that BSTABC-DCM could obtain the optimal classification accuracy and select the best representative features for the UCI problems.<\/jats:p>","DOI":"10.1155\/2020\/8864315","type":"journal-article","created":{"date-parts":[[2020,11,9]],"date-time":"2020-11-09T20:50:39Z","timestamp":1604955039000},"page":"1-13","source":"Crossref","is-referenced-by-count":6,"title":["A Binary Superior Tracking Artificial Bee Colony with Dynamic Cauchy Mutation for Feature Selection"],"prefix":"10.1155","volume":"2020","author":[{"given":"Xianghua","family":"Chu","sequence":"first","affiliation":[{"name":"College of Management, Shenzhen University, Shenzhen, China"},{"name":"Institute of Big Data Intelligent Management and Decision, Shenzhen University, Shenzhen, China"}]},{"given":"Shuxiang","family":"Li","sequence":"additional","affiliation":[{"name":"College of Management, Shenzhen University, Shenzhen, China"}]},{"given":"Da","family":"Gao","sequence":"additional","affiliation":[{"name":"College of Management, Shenzhen University, Shenzhen, China"}]},{"given":"Wei","family":"Zhao","sequence":"additional","affiliation":[{"name":"College of Management, Shenzhen University, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7293-0528","authenticated-orcid":true,"given":"Jianshuang","family":"Cui","sequence":"additional","affiliation":[{"name":"School of Economics and Management, University of Science and Technology Beijing, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0297-252X","authenticated-orcid":true,"given":"Linya","family":"Huang","sequence":"additional","affiliation":[{"name":"College of Management, Shenzhen University, Shenzhen, China"}]}],"member":"311","reference":[{"issue":"1","key":"1","first-page":"1","article-title":"The key techniques and future vision of feature selection in machine learning","volume":"41","author":"Y. 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