Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection

作者：

Highlights：

• An improved Salp Swarm Algorithm is proposed for feature selection.

• Opposition based learning was used with to improve its population diversity.

• New local search algorithm was developed to avoid local optima problem.

• A superior outperformance of the algorithm in comparison with other algorithms.

摘要

•An improved Salp Swarm Algorithm is proposed for feature selection.•Opposition based learning was used with to improve its population diversity.•New local search algorithm was developed to avoid local optima problem.•A superior outperformance of the algorithm in comparison with other algorithms.

论文关键词：Salp Swarm Algorithm,Classification,Feature selection,Optimization,Machine Learning,Algorithm,Opposition Based Learning

论文评审过程：Received 8 February 2019, Revised 28 August 2019, Accepted 3 December 2019, Available online 5 December 2019, Version of Record 13 December 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.113122