An improved method to the SVM multi-class classifier based on pairwise coupling

In this paper, an improved method is described to solve the SVM multi-class classification problem based on the pairwise coupling. As is described by Zeyu Li and his colleagues, the SVM Multi-class classifier based on pairwise coupling improves the accuracy rate while the computational cost doesn´t increase too much. By the multiple statistical analysis theory, a novel optimal weight matrix is designed to improve the accuracy rate for the less computational cost in this paper. At the end of this paper, the experimental results show the improved method is high-efficient.