Robust learning and generalization with support vector machines
Arnaud Buhot, Mirta B. Gordon · Journal of Physics A Mathematical and General · 2001
In this paper, we study the typical learning properties of the recently proposed support vector machines (SVMs). The generalization error on linearly separable tasks, the capacity, the typical number of support vectors, the margin and the robustness or noise tolerance of a class of SVMs are determined in the framework of statistical mechanics. The robustness is shown to be closely related to the generalization properties of these machines.