Probabilistic vector machine: Scalability through clustering hybridization

Abstract

In this paper, a hybrid clustering and classification algorithm is obtained by exploring the specific statistical model of a hyperplane classifier. We show how the seamless integration of the clustering component allows a substantial cost decrease in the training stage, without impairing the performance of the classifier. The algorithm is also robust to outliers and deals with training errors in a natural and efficient manner. © 2013 Springer-Verlag.