A two-layer feature selection method using Genetic Algorithm and Elastic Net

作者：

Highlights：

• A two-layer feature selection method has been proposed.

• The two layers consist of a GA-based wrapper and an Elastic Net embedded method.

• The proposed feature selection method improves the prediction accuracy.

• The feature selection method is applicable to regression problems.

摘要

•A two-layer feature selection method has been proposed.•The two layers consist of a GA-based wrapper and an Elastic Net embedded method.•The proposed feature selection method improves the prediction accuracy.•The feature selection method is applicable to regression problems.

论文关键词：Genetic Algorithms,Elastic Net,Feature selection,High-dimensional datasets

论文评审过程：Received 19 December 2019, Revised 20 September 2020, Accepted 28 September 2020, Available online 1 October 2020, Version of Record 1 October 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.114072