Weighted Linear Loss Projection Twin Support Vector Machine for Pattern Classification

Abstract

Based on the recently proposed projection twin support vector machine (PTSVM) and least squares projection twin support vector machine (LSPTSVM), in this paper, we propose a weighted linear loss projection twin support vector machine, namely WLPTSVM for short. By introducing the weighted linear loss function, the proposed WLPTSVM not only solves systems of linear equations with lower computational cost but also obtains comparable classification accuracy. In addition, it is able to dispose of large scale classification problems efficiently without any extra external optimizers. The experiments conducted on synthetic and several benchmark datasets illustrate the effectiveness of our WLPTSVM.