DocumentCode
2427686
Title
A Classification Method Based on Non-linear SVM Decision Tree
Author
Zhao, Hui ; Yao, Yong ; Liu, Zhijing
Author_Institution
Xidian Univ., Xi´´an
Volume
4
fYear
2007
fDate
24-27 Aug. 2007
Firstpage
635
Lastpage
638
Abstract
The induction of classification of decision tree is an important algorithm for data mining now. The support vector machine technology and the decision tree have combined into one multi-class classifier so as to solve multi-class classification problems. In this paper, SVM is extended to non-linear SVM by using kernel functions and a new method of NSVM decision tree is proposed based on traditional SVM decision tree. Classification experiments prove the method is effective.
Keywords
data mining; decision trees; pattern classification; support vector machines; data mining; multiclass classification problems; nonlinear SVM decision tree; support vector machine technology; Classification tree analysis; Computer science; Data mining; Decision trees; Kernel; Lagrangian functions; Quadratic programming; Statistics; Support vector machine classification; Support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2874-8
Type
conf
DOI
10.1109/FSKD.2007.6
Filename
4406464
Link To Document