Improved heuristic algorithm for support vector regression

被引：0
|
作者：
Yang Hui-zhong [1 ]
Shao Xin-guang [1 ]
Shi Chen-xi [1 ]
机构：
[1] So Yangtze Univ, Res Ctr Control Sci & Control Engn, Wuxi 214122, Peoples R China
来源：
Proceedings of 2005 Chinese Control and Decision Conference, Vols 1 and 2 | 2005年
关键词：
support vector regression; similarity measurement; heuristic rule; reducing data;
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：
Training algorithm for large-scale support vector machines is an important subject in the field of SVM research. The conventional SVM algorithm is unsuitable for large-scale problem because of the limitation of computer memory space. Aiming at the demerit of the HSVM algorithm, an improved method of heuristic training algorithm for SVM (IHSVM) based on similarity measurement is presented. The IHSVM makes use of a batch method in similarity measurement to avoid the disadvantage of HSVM. Simulating results show that IHSVM is more effective than HSVM.
引用
收藏
页码：860 / 862
页数：3
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