| 支持向量机多类分类算法新研究 |
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| 引用本文： | 余辉,赵晖.支持向量机多类分类算法新研究[J].计算机工程与应用,2008,44(7):185-189. |
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| 作者姓名： | 余辉 赵晖 |
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| 作者单位： | 1.新疆大学 信息科学与工程学院，乌鲁木齐 830046 2.北京科技大学 信息学院，北京 100083 |
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| 摘 要： | 支持向量机最初是针对两类分类问题提出的，如何将其推广至多类分类问题是当前SVM研究中的热点问题之一。主要针对支持向量机多类分类方法中的分解重构法进行了深入分析，详细讨论了影响分类器性能的两个关键因素：分解策略和组合策略，并通过实验验证了该观点。最后，通过实验对比了包括M-ary 支持向量机和模糊支持向量机的SVM多类分类方法。
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| 关 键 词： | 支持向量机 多类分类 分解重构法 |
| 文章编号： | 1002-8331（2008）07-0185-05 |
| 收稿时间： | 2007-06-18 |
| 修稿时间： | 2007-09-10 |
New research on multi-classification based on Support Vector Machines |
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| YU Hui,ZHAO Hui.New research on multi-classification based on Support Vector Machines[J].Computer Engineering and Applications,2008,44(7):185-189. |
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| Authors: | YU Hui ZHAO Hui |
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| Affiliation: | 1.College of Information Science and Engineering，Xingjinag University，Urumqi 830046，China 2.College of Information Science and Technology，University of Science and Technology Beijing，Beijing 100083，China |
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| Abstract: | Support Vector Machines(SVMs) is originally designed for binary classification.How to extend it for multi-category classification is one of hot research issues.This paper emphasizes on analyzing decomposing and reconstitution methodology of SVM multi-classification algorithms,and discusses two key factors which affect performances of categories in detail:decomposing strategy and composing strategy.The paper does experiments to validate authors' opinions and then comparesall kinds of SVM multi-category classification,including M-ary SVMs and fuzzy SVMs. |
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| Keywords: | Support Vector Machine multi-classification decomposing and reconstitution methodology |
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