A probabilistic framework for SVM regression and error bar estimation
In this paper, we elaborate on the well-known relationship between Gaussian Processes (GP) and Support Vector Machines (SVM) under some convex assumptions for the loss functions. This paper concentrates on the derivation of the evidence and error bar approximation for regression problems. An error bar formula is derived based on the epsilon -insensitive loss function.
error bar estimation gaussian process support vector machine (svm) epsilon-loss function