Regression random machines: An ensemble support vector regression model with free kernel choice

作者：

Highlights：

• Random Machines presents a new ensemble method using support vector models.

• Eliminates the choice of kernel function and simplify the tuning process.

• Discussion about the strength and diversity trade-off in ensemble learning methods.

• Success when compared its competitors in multiples artificial and real datasets.

摘要

•Random Machines presents a new ensemble method using support vector models.•Eliminates the choice of kernel function and simplify the tuning process.•Discussion about the strength and diversity trade-off in ensemble learning methods.•Success when compared its competitors in multiples artificial and real datasets.

论文关键词：Support vector regression,Bagging,Kernel functions

论文评审过程：Received 12 August 2021, Revised 23 February 2022, Accepted 28 March 2022, Available online 9 April 2022, Version of Record 29 April 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117107