An experimental evaluation of mixup regression forests

作者：

Highlights：

• In the mixup method deep learning models are trained using artificial instances.

• The instances are obtained by combining pairs of instances and their labels.

• The use of mixup in ensembles of regression trees is proposed and studied.

• The mixup approach can improve the results of Random Forest and Rotation Forest.

摘要

•In the mixup method deep learning models are trained using artificial instances.•The instances are obtained by combining pairs of instances and their labels.•The use of mixup in ensembles of regression trees is proposed and studied.•The mixup approach can improve the results of Random Forest and Rotation Forest.

论文关键词：Mixup,Regression,Random forest,Rotation forest

论文评审过程：Received 1 August 2019, Revised 20 February 2020, Accepted 10 March 2020, Available online 10 April 2020, Version of Record 10 April 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113376