Journal of Systems Engineering and Electronics 2011, 22(2) 322-326 DOI:   10.3969/j.issn.1004-4132.2011.02.020  ISSN: 1004-4132 CN: 11-3018/N

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Keywords
support vector machine (SVM)
decision tree
genetic
algorithm
classification.
Authors
PubMed

Decision tree support vector machine based on genetic algorithm
for multi-class classification

Huanhuan Chen∗, Qiang Wang, and Yi Shen

School of Astronautics, Harbin Institute of Technology, Harbin 150001, P. R. China

Abstract��

To solve the multi-class fault diagnosis tasks, decision
tree support vector machine (DTSVM), which combines SVM
and decision tree using the concept of dichotomy, is proposed.
Since the classification performance of DTSVM highly depends on
its structure, to cluster the multi-classes with maximum distance
between the clustering centers of the two sub-classes, genetic algorithm
is introduced into the formation of decision tree, so that the
most separable classes would be separated at each node of decisions
tree. Numerical simulations conducted on three datasets
compared with “one-against-all” and “one-against-one” demonstrate
the proposed method has better performance and higher
generalization ability than the two conventional methods.

Keywords�� support vector machine (SVM)   decision tree   genetic
algorithm
   classification.  
Received  Revised  Online:  
DOI: 10.3969/j.issn.1004-4132.2011.02.020
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