Decision tree support vector machine

被引：43
|
作者：
Zhang, Li [1 ]
Zhou, Wei-Da [1 ]
Su, Tian-Tian [1 ]
Jiao, Li-Cheng [1 ]
机构：
[1] Xidian Univ, Inst Intelligence Informat Proc, Xian 710071, Peoples R China
来源：
INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS | 2007年 / 16卷 / 01期
关键词：
support vector machines; decision tree; multi-class classification;
D O I：
10.1142/S0218213007003163
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new multi class classifier decision tree SVM (DTSVM) which is a binary decision tree with a very simple structure is presented in this paper. In DTSVM, a problem of multi class classification is decomposed into a senes of ones of binary classification. Here, the binary decision tree is generated by using kernel clustering algorithm, and each non-leaf node represents one binary classification problem. By compared with the other multi-class classification methods based on the binary classification SVMs, the scale and the complexity of DTSVM are less, smaller number of support vectors are needed, and has faster test speed. The final simulation results confirm the feasibility and the validity of DTSVM.
引用
收藏
页码：1 / 15
页数：15
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