Fuzzy Support Vector Machines with Automatic Membership Setting

Abstract

Support vector machines like other classification approaches aim to learn the decision surface from the input points for classification problems or regression problems. In many applications, each input points may be associated with different weightings to reflect their relative strengths to conform to the decision surface. In our previous research, we applied a fuzzy membership to each input point and reformulate the support vector machines to be fuzzy support vector machines (FSVMs) such that different input points can make different contributions to the learning of the decision surface.