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| 支持向量机的SMO算法及其自适应改进研究 | |
| 引用本文： | 王伟,刘梅,段爱玲.支持向量机的SMO算法及其自适应改进研究[J].河南科学,2010,28(4):436-439. |
| 作者姓名： | 王伟 刘梅 段爱玲 |
| 作者单位： | 1. 武汉理工大学,计算机科学与技术学院,武汉,430070;郑州牧业工程高等专科学校信息工程系,郑州,450011 2. 郑州牧业工程高等专科学校信息工程系,郑州,450011 3. 河南工业大学信息科学与工程学院,郑州,450001 |
| 基金项目： | 河南省教育厅自然科学研究计划项目 |
| 摘 要： | 提出在SMO算法上应用自适应学习的思想,并利用求解凸二次规划寻优问题的基础上进行改进的研究.研究表明,基于自适应学习的思想对SMO算法进行改进,可使SVM算法更能适应实际应用快速、高效的需求. |
| 关 键 词： | 机器学习 支持向量机 SMO算法 自适应 |
The Algorithm Research on Support Vector Machine and Adaptive SMO Improvement |
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| Wang Wei,Liu Mei,Duan Ailing.The Algorithm Research on Support Vector Machine and Adaptive SMO Improvement[J].Henan Science,2010,28(4):436-439. | |
| Authors: | Wang Wei Liu Mei Duan Ailing |
| Institution: | 1. College of Computer Science and Technology, Wuhan University of Technology, Wuhan 430070, China; 2. Department of Information Engineering, Zhengzhou College of Animal Husbandry Engineering, Zhengzhou 450011, China; 3. College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China) |
| Abstract: | Support vector machine （SVM）is an important kind of statistical machine learning algorithm,which SMO algorithm is effective in practical application. SMO is based on support vector machine to solve quadratic progra- mming problem into a set of smaller problems, so as to achieve the minimum serial. The proposed method is applied in SMO algorithm of adaptive learning ideas, and the improvement on the basis of using the optimum solution convex quadratic programming problem. Therefore, SMO algorithm based on the idea of the adaptive learning has been improved SMO. And it will enable the SVM algorithm to adapt to the practical application of fast and efficient needs. |
| Keywords: | machine learning support vector machine SMO algorithm adaptive |
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