Hybrid filter-wrapper feature selection using whale optimization algorithm: A multi-objective approach

作者：

Highlights：

• A novel multi-objective feature selection algorithm is proposed.

• It hybridizes filter and wrapper models into whale optimization algorithm.

• It has been validated through ten datasets and compared against five algorithms.

• Yields solutions with fewer features and improves the classification accuracy.

摘要

•A novel multi-objective feature selection algorithm is proposed.•It hybridizes filter and wrapper models into whale optimization algorithm.•It has been validated through ten datasets and compared against five algorithms.•Yields solutions with fewer features and improves the classification accuracy.

论文关键词：Feature selection,Filter and wrapper approaches,Multi-objective optimization,Whale optimization algorithm (WOA)

论文评审过程：Received 10 November 2020, Revised 29 April 2021, Accepted 30 May 2021, Available online 8 June 2021, Version of Record 16 June 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115312