Enhanced Crow Search Algorithm for Feature Selection

作者：

Highlights：

• Apply the enhanced crow search algorithm used as Feature selection approach.

• Dynamic local neighborhood and adaptive awareness probability used to improve CSA.

• Evaluate the performance of the proposed method using a set of UCI machine datasets.

• Developed approach outperforms other feature selection approaches.

摘要

•Apply the enhanced crow search algorithm used as Feature selection approach.•Dynamic local neighborhood and adaptive awareness probability used to improve CSA.•Evaluate the performance of the proposed method using a set of UCI machine datasets.•Developed approach outperforms other feature selection approaches.

论文关键词：Feature selection,Crow search algorithm (CSA),Metaheuristic,Dynamic local neighborhood,Adaptive awareness probability

论文评审过程：Received 28 December 2019, Revised 26 March 2020, Accepted 14 May 2020, Available online 6 June 2020, Version of Record 11 June 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113572