A fuzzy penalized regression model with variable selection

作者：

Highlights：

• Fuzzy penalized regression model.

• Fuzzy output variable and crisp input variables.

• Optimal iterative solutions.

• Variable selection criterion for relevant input variables.

• Unified approach for multicollinearity and variable selection.

摘要

•Fuzzy penalized regression model.•Fuzzy output variable and crisp input variables.•Optimal iterative solutions.•Variable selection criterion for relevant input variables.•Unified approach for multicollinearity and variable selection.

论文关键词：Fuzzy regression,Penalized model,Least-squares method,Bootstrap-t confidence interval,Uncertainty measure,Variable selection

论文评审过程：Received 9 May 2020, Revised 4 December 2020, Accepted 6 February 2021, Available online 13 February 2021, Version of Record 16 March 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.114696