Second Order Cone Programming Formulations for Robust Support Vector Ordinal Regression Machine
Zhixia Yang, Yingjie Tian, Nai-Yang Deng · 2007
Abstract Support vector ordinal regression machine (SVORM) is an effective method for ordinal regression problem. Up to now, the SVORM implicitly assumes the training data to be known exactly. However, in practice, the training data subject to measurement noise. In this paper, we propose a robust version of SVORM. The robustness of the proposed method is validated by our preliminary numerical experiments. 1