A total multi-class support vector machine

作者：Xu Yitian^*; Wu Cong

来源：Journal of Information and Computational Science, 2011, 8(7): 1147-1154.

• Benchmark datasets
• Hyper-plane
• K-SVCR
• Multi-class classification
• Multi-class support vector machines
• Prediction accuracy
• Support vector
• Total K-SVCR

A new multi-class classification algorithm, called total K-SVCR, is proposed in this paper. The proposed algorithm not only makes the correctly classified samples as far as possible from the classification hyper-plane, but also makes the misclassified samples as close as possible to it, which could avoid the disturbance of noises or outliers to a certain degree. Compared with K-SVCR on four benchmark datasets, the proposed algorithm yields higher prediction accuracy and costs lower. It demonstrates the feasibility and validity of the proposed algorithm.

• 出版日期2011
• 单位中国农业大学