Optimization of Multi-class SVM Binary Tree based on Binary PSO

摘要：

Multi-class SVM classification binary tree has the problem of error accumulation,the classification error caused by the upper node of the binary tree cant be corrected by the following nodes,this problem reduce the classification accuracy. In order to overcome the error accumulation produced by the binary tree of SVM multi-class classification,the binary PSO algorithm (BPSO) was introduced to optimize every node of multi-class SVM classification binary tree by designing particles encoding and fitness function of binary PSO algorithm and building the binary tree during the optimization process. Experiments show that the multi-class SVM classification binary tree optimized by the binary PSO achieves better multi-class classification accuracy,and the binary BPSO reduces the time needed to optimize binary tree.

关键词： binary PSO SVM multi-class classification binary tree

作者: Liang Zhengyou Chang Shuai Tang Yixuan

作者单位: School of Computer and Electronic Information,Guangxi University,Nanning 530004,China

会议类型: 国际会议

会议名称: 2010 International Forum on Computer Science-Technology and Applications(2010 国际计算机科学技术应用论坛 IFCSTA 2010)

会议地点: 南宁

会议语种:英文

页码: 66-69

在线出版日期: 2010-12-10（万方平台首次上网日期，不代表论文的发表时间）