Title :
A Classification Method Based on Non-linear SVM Decision Tree
Author :
Zhao, Hui ; Yao, Yong ; Liu, Zhijing
Author_Institution :
Xidian Univ., Xi´´an
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;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.6
