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| An extended Lagrangian support vector machine for classifications | |
| 作者姓名： | YANG Xiaowei SHU Lei HAO Zhifeng LIANG Yanchun LIU Guirong HAN Xu |
| 作者单位： | Department of Applied Mathematics, South China University of Technology, Guangzhou 510640, China;Centre for ACES, Department of Mechanical Engineering, National University of Singapore, 119260, Singapore,Department of Applied Mathematics, South China University of Technology, Guangzhou 510640, China,Department of Applied Mathematics, South China University of Technology, Guangzhou 510640, China,College of Computer Science and Technology, Jilin University, Changchun 130012, China,Centre for ACES, Department of Mechanical Engineering, National University of Singapore, 119260, Singapore,Centre for ACES, Department of Mechanical Engineering, National University of Singapore, 119260, Singapore |
| 基金项目： | 国家自然科学基金，教育部重点工程基金，广东省自然科学基金，教育部优秀青年教师资助计划，华南理工大学校科研和教改项目 |
| 摘 要： | Lagrangian support vector machine (LSVM) cannot solve large problems for nonlinear kernel classifiers. In order to extend the LSVM to solve very large problems, an extended Lagrangian support vector machine (ELSVM) for classifications based on LSVM and SVMlight is presented in this paper. Our idea for the ELSVM is to divide a large quadratic programming problem into a series of subproblems with small size and to solve them via LSVM. Since the LSVM can solve small and medium problems for nonlinear kernel classifiers, the proposed ELSVM can be used to handle large problems very efficiently. Numerical experiments on different types of problems are performed to demonstrate the high efficiency of the ELSVM. |
| 关 键 词： | quadratic programming support vector machine decomposition algorithm LSVM ELSVM |
An extended Lagrangian support vector machine for classifications |
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| YANG Xiaowei,SHU Lei,HAO Zhifeng,LIANG Yanchun,LIU Guirong,HAN Xu.An extended Lagrangian support vector machine for classifications[J].Progress in Natural Science,2004,14(6):519-523. | |
| Authors: | Yang Xiaowei SHU Lei HAO Zhifeng LIANG Yanchun LIU Guirong HAN Xu |
| Institution: | 1. Department of Applied Mathematics, South China University of Technology, Guangzhou 510640, China;Centre for ACES, Department of Mechanical Engineering, National University of Singapore, 119260, Singapore 2. Department of Applied Mathematics, South China University of Technology, Guangzhou 510640, China 3. College of Computer Science and Technology, Jilin University, Changchun 130012, China 4. Centre for ACES, Department of Mechanical Engineering, National University of Singapore, 119260, Singapore |
| Abstract: | Lagrangian support vector machine (LSVM) cannot solve large problems for nonlinear kernel classifiers. In order to extend the LSVM to solve very large problems, an extended Lagrangian support vector machine (ELSVM) for classifications based on LSVM and SVMlight is presented in this paper. Our idea for the ELSVM is to divide a large quadratic programming problem into a series of subproblems with small size and to solve them via LSVM. Since the LSVM can solve small and medium problems for nonlinear kernel classifiers, the proposed ELSVM can be used to handle large problems very efficiently. Numerical experiments on different types of problems are performed to demonstrate the high efficiency of the ELSVM. |
| Keywords: | quadratic programming support vector machine decomposition algorithm LSVM ELSVM |
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