Robust twin support vector regression via second-order cone programming
作者:
Highlights:
• Novel robust approach for twin SVR using second-order cone programming.
• A geometrically grounded method based on the concept of ellipsoids.
• Superior performance is achieved in experiments on benchmark datasets.
摘要
•Novel robust approach for twin SVR using second-order cone programming.•A geometrically grounded method based on the concept of ellipsoids.•Superior performance is achieved in experiments on benchmark datasets.
论文关键词:Support vector regression,Twin support vector machines,Second-order cone programming,Robust optimization
论文评审过程:Received 9 September 2017, Revised 1 April 2018, Accepted 2 April 2018, Available online 3 April 2018, Version of Record 12 May 2018.
论文官网地址:https://doi.org/10.1016/j.knosys.2018.04.005