A Multi-class Algorithm Model Based on p-class Support Vector Ordinal Regression Machine

摘要：

Multi-class classification is an important and on-going research subject in machine learning. In this paper, we propose an algorithm model for k-class multi-class classification problem based on p-class (2 ≤ p ≤ k) support vector ordinal regression machine (SVORM). A series of algorithms can be generated by selecting the different parameters p, L and the code matrix. When p = 2, they reduce to the popular algorithms based on 2-class SVMs. When p = 3, they improve K-SVCR in 1 and v-K-SVCR in 18. The algorithms based on p-class SVORM in this algorithm model are more interesting because our preliminary numerical experiments show that then are promising. At last, some problems for further study are suggested.

关键词： Multi-class classification problem decomposition-reconstruction support vector ordinal regression machine error-correcting output code.

作者: Zhi-Xia Yang

作者单位: College of Mathematics and System Science, Xinjiang University, Urumuchi 830046 Academy of Mathematics and Systems Science, CAS, Beijing 100190

会议类型: 国际会议

会议名称: The Second International Symposium(OSB08)(第二届国际优化及系统生物学学术会议)

会议地点: 云南丽江

会议语种:英文

页码: 54-61

在线出版日期: 2008-10-31（万方平台首次上网日期，不代表论文的发表时间）