A novel multi-class SVM classifier based on DDAG

被引：0

作者：

Li, KL ^{[1
]}

Huang, HK ^{[1
]}

Tian, SF ^{[1
]}

机构：

[1] No Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China

来源：

2002 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-4, PROCEEDINGS | 2002年

关键词：

support vector machine; multi-class classification problem; active constraint; decision directed acyclic graph;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a new method of constructing multi-class SVM classifier, which is based on the structure of Decision Directed Acyclic Graph (DDAG) and using active constraint for each SVM classifier. For k-class problem, it combines k(k-1)/2 two-class SVM classifiers, one for each pair of classes. In order to speed up the training and decision process of the classifier, we make three changes on the standard two-class classifiers, i.e. large margin, 2-norm squared for the error for the soft margin and active constraint. While in the testing phase, we use a rooted binary directed acyclic graph which has k(k-1)12 internal nodes and k leaves. Computational experiment indicates that this is a simple and fast approach to generate multi-class SVM classifiers.

引用

页码：1203 / 1207

页数：5