Oblique Decision Tree Ensemble via Twin Bounded SVM

作者：

Highlights：

• A novel approach is proposed to generate the oblique decision tree ensemble via TBSVM.

• Structural risk minimization principle is implemented in the proposed models.

• No explicit regularization techniques need to be applied in the proposed models.

• Experimental results and statistical tests show the efficacy of the proposed models.

摘要

•A novel approach is proposed to generate the oblique decision tree ensemble via TBSVM.•Structural risk minimization principle is implemented in the proposed models.•No explicit regularization techniques need to be applied in the proposed models.•Experimental results and statistical tests show the efficacy of the proposed models.

论文关键词：Oblique,Ensemble,Decision trees,Random forest (RaF),Rotation forest (RoF),Twin bounded support vector machine (TBSVM)

论文评审过程：Received 16 July 2019, Revised 6 October 2019, Accepted 1 November 2019, Available online 9 November 2019, Version of Record 21 November 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.113072