关键词: 支持向量机, 支持向量回归机, r范数损失函数

Abstract: The dependency relationship between r and the input noise in r-SVR is studied using SVR Bayesian evidence framework.First，focus is paid on the cases of laplacian noise and uniform noise，and the approximately inversely linear dependencies between r and the variances of the two noises are then respectively derived.Second，with the relevant conclusion on r-SVR and experimental study，the more general claim is then proposed that the approximately inversely linear dependency is almost kept between r and the input noise in r-SVR.Such a dependency relationship is useful to determine the optimal choice for r in Norm-r loss function in the existence of unknown input noise.

Key words: Support Vector Machines（SVM）, Support Vector Regression（SVR）, Norm-r function