Chaotic binary Group Search Optimizer for feature selection

作者：

Highlights：

• A novel feature selection method is proposed for classification task.

• Five Chaotic Group Search Optimizers are investigated.

• Twenty UCI datasets were used in the experiments.

• Our methods got a higher accuracy results using a fewer number of features.

摘要

•A novel feature selection method is proposed for classification task.•Five Chaotic Group Search Optimizers are investigated.•Twenty UCI datasets were used in the experiments.•Our methods got a higher accuracy results using a fewer number of features.

论文关键词：Group Search Optimizer (GSO),Chaotic maps,Feature selection (FS),Optimization problem,Meta-heuristic algorithm

论文评审过程：Received 10 May 2020, Revised 26 June 2021, Accepted 30 November 2021, Available online 20 December 2021, Version of Record 1 January 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116368