Robust one-class support vector machine with rescaled hinge loss function

作者：

Highlights：

• A novel robust one-class support vector machine (OCSVM) based on the rescaled hinge loss function is proposed;

• The optimization problem of the proposed robust OCSVM is iteratively solved by the half-quadratic optimization technique;

• The generalization performance of robust OCSVM is analyzed from the theoretical analysis;

• The robustness of robust OCSVM is explained from the weighted viewpoint.

摘要

•A novel robust one-class support vector machine (OCSVM) based on the rescaled hinge loss function is proposed;•The optimization problem of the proposed robust OCSVM is iteratively solved by the half-quadratic optimization technique;•The generalization performance of robust OCSVM is analyzed from the theoretical analysis;•The robustness of robust OCSVM is explained from the weighted viewpoint.

论文关键词：One-class classification,One-class support vector machine,Hinge loss function,Half-quadratic optimization

论文评审过程：Received 21 January 2018, Revised 15 May 2018, Accepted 10 July 2018, Available online 12 July 2018, Version of Record 19 July 2018.

论文官网地址：https://doi.org/10.1016/j.patcog.2018.07.015