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| 最小二乘支持向量机分类问题的算法实现 | |
| 引用本文： | 周建萍,郑应平,王志萍.最小二乘支持向量机分类问题的算法实现[J].上海电力学院学报,2008,24(4):381-384. |
| 作者姓名： | 周建萍 郑应平 王志萍 |
| 作者单位： | 1. 上海电力学院,电力与自动化工程学院,上海,200090;同济大学,电子与信息工程学院,上海,200092 2. 同济大学,电子与信息工程学院,上海,200092 3. 上海电力学院,电力与自动化工程学院,上海,200090 |
| 基金项目： | 上海高校选拔培养优秀青年教师科研专项基金 ， 上海市重点学科建设项目 |
| 摘 要： | 介绍了支持向量机理论、常用的支持向量机内积核函数以及最小二乘支持向量机算法.采用最小二乘法实现了支持向量机分类算法.数字仿真结果表明,该算法的识别正确率可达100%. |
| 关 键 词： | 最小二乘法 支持向量机 核函数 分类 |
| 收稿时间： | 2008/2/22 0:00:00 |
Arithmetic Realization of Least Square Support Vector Machine Classification |
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| ZHOU Jian-ping,ZHENG Ying-ping and WANG Zhi-ping.Arithmetic Realization of Least Square Support Vector Machine Classification[J].Journal of Shanghai University of Electric Power,2008,24(4):381-384. | |
| Authors: | ZHOU Jian-ping ZHENG Ying-ping and WANG Zhi-ping |
| Affiliation: | School of Electric Power & Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China;School of Electronics & Information, Tongji University, Shanghai 200092, China,School of Electronics & Information, Tongji University, Shanghai 200092, China and School of Electric Power & Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China |
| Abstract: | Theories of support vector machine(SVM),the kernel function of commouly-used(SVM),and the least square algorithm support vector are introduced.Support vector machine classification is realized by least square algorithm and numerical simulation is performed.Simulation results show that recognition rate of the proposed method is up to 100%. |
| Keywords: | least square algorithm support vector machine(SVM) kernel function classification |
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