Novel optimized crow search algorithm for feature selection

作者：

Highlights：

• Improve the balance between the local and global search.

• Introducing a new neighborhood concept for improving the local search.

• Proposing a new method to search more purposeful during exploration.

• Increasing convergence rate using chaos.

• Being pioneer in reducing the dataset volume.

摘要

•Improve the balance between the local and global search.•Introducing a new neighborhood concept for improving the local search.•Proposing a new method to search more purposeful during exploration.•Increasing convergence rate using chaos.•Being pioneer in reducing the dataset volume.

论文关键词：Feature selection,Crow search algorithm,Metaheuristic method,Feature reduction,Classification

论文评审过程：Received 27 February 2021, Revised 5 April 2022, Accepted 30 April 2022, Available online 14 May 2022, Version of Record 20 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117486