A new hybrid approach for feature selection and support vector machine model selection based on self-adaptive cohort intelligence

作者：

Highlights：

• The limitations of cohort intelligence algorithm are identified.

• A new variation of cohort intelligence algorithm is proposed.

• The proposed algorithm employs self-adaptive scheme and mutation operator.

• A new hybrid approach for feature selection and SVM model selection is proposed.

• The proposed algorithm outperforms the original cohort intelligence algorithm.

摘要

•The limitations of cohort intelligence algorithm are identified.•A new variation of cohort intelligence algorithm is proposed.•The proposed algorithm employs self-adaptive scheme and mutation operator.•A new hybrid approach for feature selection and SVM model selection is proposed.•The proposed algorithm outperforms the original cohort intelligence algorithm.

论文关键词：Feature selection,SVM,Classification,Cohort intelligence,Metaheuristic

论文评审过程：Received 24 December 2016, Revised 18 June 2017, Accepted 19 June 2017, Available online 24 June 2017, Version of Record 4 July 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.06.030