A pareto-based ensemble of feature selection algorithms
作者：
Highlights：
• We have designed a method for ensemble feature selection.
• We model the feature selection process to a Pareto-based optimization problem.
• The crowding distance between solutions is the secondary measure.
• The method is an ensemble of relevancy and redundancy methods.
• The proposed PEFS method outperforms competitive algorithms.
摘要
•We have designed a method for ensemble feature selection.•We model the feature selection process to a Pareto-based optimization problem.•The crowding distance between solutions is the secondary measure.•The method is an ensemble of relevancy and redundancy methods.•The proposed PEFS method outperforms competitive algorithms.
论文关键词：Ensemble feature selection,Pareto-based method,Bi-objective optimization,Crowding distance
论文评审过程：Received 18 April 2020, Revised 13 March 2021, Accepted 26 April 2021, Available online 30 April 2021, Version of Record 8 May 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115130
