The application of least squares support vector machine for classification

被引：0
|
作者：
Liu, Bo [1 ]
Hao, Zhifeng [1 ]
Yang, Xiaowei [1 ]
机构：
[1] S China Univ Technol, Coll Comp Sci & Engn, Guangzhou 510640, Peoples R China
来源：
ADVANCES IN MATRIX THEORY AND APPLICATIONS | 2006年
关键词：
support vector machine; least squares support vector machine; machine learning;
D O I：
暂无
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In the training of stand support vector machine, the issue is reformulated and represented in such a way so as to obtain a quadratic programming problem. In order to solve the problems expediently, the Least squares support vector machines (LS-SVMs) was introduced. In which, one uses the equality constraints instead of inequality in the conventional SVMs, in this way the optimal solution can be obtained by solving a set of linear equations instead of solving a quadratic programming problem. In the paper, we imply the LS-SVMs into a real data set, the results show the good performance of the LS-SVMs.
引用
收藏
页码：265 / 268
页数：4
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