| 树形结构SVMs多类分类的研究 |
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| 引用本文： | 王春歆,李连,张玉叶.树形结构SVMs多类分类的研究[J].海军航空工程学院学报,2005,20(2):254-256. |
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| 作者姓名： | 王春歆 李连 张玉叶 |
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| 作者单位： | 海军航空工程学院研究生管理大队，海军航空工程学院控制工程系，海军航空工程学院研究生管理大队 烟台，264001 |
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| 摘 要： | 介绍了SVM方法原理,为了将SVM在解决两类分类问题中的优越性推广至解决多类分类问题,分析构建树方法与SVM结合运用来提高SVM在进行多类分类时的训练效率的方法, 然后构造文本自动分类,实验说明该方法有较高的训练效率,并且所需的训练样本量大大降低。
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| 关 键 词： | 支持向量机 决策树 多类分类 |
| 修稿时间： | 2004年12月20 |
Research of SVMs Multi-Category Classification in Decision Tree |
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| WANG Chun-xin,LI Lian,ZHANG Yu-ye Graduate Students'Brigade of NAEI.Research of SVMs Multi-Category Classification in Decision Tree[J].Journal of Naval Aeronautical Engineering Institute,2005,20(2):254-256. |
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| Authors: | WANG Chun-xin LI Lian ZHANG Yu-ye Graduate Students'Brigade of NAEI |
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| Institution: | WANG Chun-xin,LI Lian,ZHANG Yu-ye Graduate Students'Brigade of NAEI Department of Control Engineering,NAEI,Yantai,264001 |
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| Abstract: | This paper introduces the theory of Support Vector Machine (SVM) . In order to extend the advantage of SVM in solving binary classification to multi-category classification, it analyzes the method of combining SVM with the method constructing tree to improve the training efficiency in multi-category classification. And it performs a text classification experiment to prove that it not only has high training efficiency, but also greatly reduces the number of samples. |
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| Keywords: | support vector machine (SVM) decision tree multi-category classification |
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