The support vector method

Abstract

The Support Vector (SV) method is a new general method of function estimation which does not depend explicitly on the dimesionality of input space. It was applied for pattern recognition, regression estimation, and density estimation problems as well as for problems of solving linear operator equations. In this article we describe the general idea of the SV method and present theorems demonstrating that the generalization ability of the SV method is based c factors which classical statistics do not take into account. We ah describe the SV method for density estimation in a set of function defined by a mixture of an infinite number of Gaussians.