A Binary Superior Tracking Artificial Bee Colony with Dynamic Cauchy Mutation for Feature Selection

Xianghua Chu, Shuxiang Li, Da Gao, Wei Zhao, Jianshuang Cui and Linya Huang

Complexity, 2020, vol. 2020, 1-13

Abstract:

This paper aims to propose an improved learning algorithm for feature selection, termed as binary superior tracking artificial bee colony with dynamic Cauchy mutation (BSTABC-DCM). 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.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:8864315

DOI: 10.1155/2020/8864315

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