A Multi-class Classification Algorithm based on Ordinal Regression Machine
Zhixia Yang, Nai-Yang Deng, Yingjie Tian · 2006
Multi-class classification is an important and on-going research subject in machine learning. In this paper, we propose a multi-class classification algorithm based on ordinal regression algorithm using 3-class classification. This algorithm is similar to Algorithm K-SVCR and Algorithm v- K-SVCR, but it includes fewer parameters. Another advantage of our algorithm is that, for the K-class classification problem, our algorithm can be extended to using p-class classification with 2 \lt p \gt K. Numerical experiments on artificial data sets and benchmark data sets show that the algorithm is reasonable and effective.