Decision Tree Twin Support Vector Machine Based on Kernel Clustering for Multi-class Classification

2018 ◽  
pp. 293-303 ◽  
Author(s):  
Qingyun Dou ◽  
Li Zhang
Keyword(s):  
Support Vector Machine ◽  
Decision Tree ◽  
Twin Support Vector Machine ◽  
Support Vector ◽  
Kernel Clustering ◽  
Multi Class Classification

scholarly journals The Best Separating Decision Tree Twin Support Vector Machine for Multi-Class Classification

2013 ◽  
Vol 17 ◽  
pp. 1032-1038 ◽  
Author(s):  
Yuan-Hai Shao ◽  
Wei-Jie Chen ◽  
Wen-Biao Huang ◽  
Zhi-Min Yang ◽  
Nai-Yang Deng
Keyword(s):  
Support Vector Machine ◽  
Decision Tree ◽  
Twin Support Vector Machine ◽  
Support Vector ◽  
Multi Class Classification

DECISION TREE SUPPORT VECTOR MACHINE

2007 ◽  
Vol 16 (01) ◽  
pp. 1-15 ◽  
Author(s):  
LI ZHANG ◽  
WEI-DA ZHOU ◽  
TIAN-TIAN SU ◽  
LI-CHENG JIAO
Keyword(s):  
Decision Tree ◽  
Clustering Algorithm ◽  
Binary Classification ◽  
Classification Problem ◽  
Support Vector ◽  
Binary Decision ◽  
Binary Decision Tree ◽  
Kernel Clustering ◽  
Binary Classification Problem ◽  
Multi Class Classification

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 series 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.

Study on Housing Performance Evaluation Model Based on Hierarchical Potential Support Vector Machine

2011 ◽  
Vol 90-93 ◽  
pp. 894-898
Author(s):  
Bo Jing Tian
Keyword(s):  
Support Vector Machine ◽  
Feature Selection ◽  
Performance Evaluation ◽  
Decision Tree ◽  
Qualitative Analysis ◽  
Supplier Selection ◽  
Evaluation Model ◽  
Support Vector ◽  
Performance Evaluation Model ◽  
Multi Class Classification

Housing performance is an important and widely studied topic since it has significant impact on architecture design and programming. In terms of problems existing in the field, a new support vector machine technology, potential support vector machine, is introduced and then combined with decision tree to address issues on supplier selection including feature selection, multi-class classification and so on. And the methodology proposed in the paper, which is proved to the strengthens of integrating knowledge and experiences from experts in the paper, can be applied in housing performance evaluation which is one of complex issues combined with processes including not only quantitative, but also qualitative analysis.

Sign in / Sign up

Export Citation Format

Share Document