| 多类支持向量机分类算法—DDAG① |
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| 引用本文： | 汪政,邵良杉.多类支持向量机分类算法—DDAG①[J].计算机系统应用,2010,19(7):87-90. |
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| 作者姓名： | 汪政 邵良杉 |
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| 作者单位： | 辽宁工程技术大学,电信学院,辽宁,葫芦岛,125105 |
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| 摘 要： | 随着支持向量机的发展，由最初的两类分类问题逐渐推广到多类分类问题，且其思想、算法多种多样，各有千秋。主要研究以当前比较流行的以多个二类分类器组合实现多类分类器的算法之一：DDAG。提出此算法在多类支持向量机应用分类中存在的优点和不足，并针对其不足，提出一种改进的算法思想。
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| 关 键 词： | 数据挖掘 支持向量机 分类算法 DDAG |
| 收稿时间： | 2009/10/21 0:00:00 |
| 修稿时间： | 2009/11/14 0:00:00 |
Categorization Algorithms Based on M-SVMs-DDAG |
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| WANG Zheng and SHAO Liang-Shan.Categorization Algorithms Based on M-SVMs-DDAG[J].Computer Systems& Applications,2010,19(7):87-90. |
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| Authors: | WANG Zheng and SHAO Liang-Shan |
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| Affiliation: | (Department of Electronic and Information Engineering, Liaoning Techinical University of China, Huludao 125105, China) |
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| Abstract: | With the development of SVM, its application has been extended from binary class classification problem to multi-class classification problems. Its concepts and algorithms become various and different. The main study in this paper is DDAG, which is one of the popular algorithms, whose principle is combining the binary class classifiers with multi-class classifiers. This paper also points out the strengths and weaknesses of DDAC, when it is used in multi-class SVM text classification, and presents an improved algorithmic concept to make up for the weaknesses. |
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| Keywords: | DDAG |
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