5 If we choose R from a family of sufficiently "gradual" functions, then similar items necessarily receive similar labels.
we consider linear, S -insensitive SVM regression (Vapnik, 1995;Smola and Schölkopf, 1998); the idea is to find the hyperplane that best fits the training data, but where training points whose labels are within distance S of the hyperplane incur no loss.