Critical vector learning for text categorisation

Abstract

This paper proposes a new text categorisation method based on the critical vector learning algorithm. By using the proposed approach, the number of support vectors has been significantly reduced by implementing a Bayesian treatment of a generalised linear model with identical function form to the function form of support vector machines approach. This leads to much reduced computational complexity in the prediction process, which is critical in online applications.