Robust Kernel-Based Regression

In this research, a robust optimization approach applied to support vector regression (SVR) is investigated. A novel ker-nel based-method is developed to address the problem of data uncertainty where each data point is inside a sphere. The model is called robust SVR. Computational results show that the resulting robust SVR model is better than traditional SVR in terms of robustness and generalization error