A hybrid fuzzy feature selection algorithm for high-dimensional regression problems: An mRMR-based framework

作者：

Highlights：

• A hybrid fuzzy feature selection algorithm for high-dimensional regression problems.

• A filter-based Selector.

• A wrapper-based Modifier.

• Evaluation using 28 real-world regression datasets and different FRBSs.

摘要

•A hybrid fuzzy feature selection algorithm for high-dimensional regression problems.•A filter-based Selector.•A wrapper-based Modifier.•Evaluation using 28 real-world regression datasets and different FRBSs.

论文关键词：Hybrid feature selection,Fuzzy mutual information,Minimum Redundancy Maximum Relevance,Fuzzy rule-based systems,High-dimensional regression problems

论文评审过程：Received 28 September 2019, Revised 7 July 2020, Accepted 6 August 2020, Available online 14 August 2020, Version of Record 10 October 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113859