| 支持向量机及其应用研究 |
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| 引用本文： | 罗雪晖,李霞,张基宏.支持向量机及其应用研究[J].深圳大学学报(理工版),2003,20(3):40-46. |
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| 作者姓名： | 罗雪晖 李霞 张基宏 |
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| 作者单位： | 深圳大学信息工程学院,深圳,518060 |
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| 基金项目： | 国家自然科学基金(60172065) |
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| 摘 要： | 支持向量机是一种新型机器学习方法,因其出色的学习性能,已成为当前国际机器学习界的研究热点.作者介绍了支持向量机的理论依据及其研究进展.
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| 关 键 词： | 机器学习 统计学习理论 支持向量机 模式识别 |
| 文章编号： | 1000-2618(2003)03-0040-07 |
| 修稿时间： | 2003年4月18日 |
Introduction to Support Vector Machine and Its Applications |
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| LUO Xue-hui,LI Xia and ZHANG Ji-hong
College of Information Engineering
Shenzhen University
Shenzhen
P. R. China.Introduction to Support Vector Machine and Its Applications[J].Journal of Shenzhen University(Science &engineering),2003,20(3):40-46. |
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| Authors: | LUO Xue-hui LI Xia and ZHANG Ji-hong
College of Information Engineering
Shenzhen University
Shenzhen
P R China |
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| Affiliation: | LUO Xue-hui,LI Xia and ZHANG Ji-hong
College of Information Engineering
Shenzhen University
Shenzhen 518060
P. R. China |
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| Abstract: | Support vector machine ( SVM) , a novel machine learning method, has become a hotspot because of its excellent learning performance. This paper introduces the fundamental theory underlying the SVM, its current state-of-the-art as well as its applications in pattern recognition. |
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| Keywords: | machine learning statistical learning theory support vector machine pattern recognition |
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