An Efficient Algorithm for Multi-class Support Vector Machines
Jun Guo, Norikazu Takahashi, Wenxin Hu · 2008
A novel algorithm for multi-class support vector machines (SVMs) is proposed in this paper. The tree constructed in our algorithm consists of a series of two-class SVMs. Considering both separability and balance, in each iteration multi-class patterns are divided into two sets according to the distances between pairwise classes and the number of patterns in each class. This algorithm can well treat with the unequally distributed problems. The efficiency of the proposed method are verified by the experimental results.