A Robust Formulation for Support Vector Regression

摘要

This paper investigates a new support vector regression model in which the observed data are corrupted with noise.We present a second-order cone programming formulation for designing robust regression which can handle uncertainty in data.Empirical results are included to show that the robust model is superior to the standard model.