Title :
Weighted multi-class support vector machine based on binary tree
Author :
Mi, Xiao-ya ; Ha, Ming-Hu ; Chen, Xu
Author_Institution :
Coll. of Math. & Comput. Sci., Hebei Univ., Baoding, China
Abstract :
A classification algorithm of the multi-class SVM based on binary tree is inducted in this paper and its advantages and defections are analyzed. To overcome its defections, a new weighted multi-class SVM based on binary tree is proposed. Furthermore the proposed method can be applied to the case of regarding small sort of classification accuracy, such as fault diagnosis. Finally the experiment results show that it has higher classification accuracy than that of the traditional multi-class SVM based on the binary tree.
Keywords :
pattern classification; support vector machines; trees (mathematics); binary tree; classification algorithm; fault diagnosis; weighted multiclass support vector machine; Binary trees; Classification tree analysis; Computer science; Cybernetics; Decision making; Educational institutions; Machine learning; Mathematics; Support vector machine classification; Support vector machines; Binary tree; Multi-class classification; Weighted support vector machine;
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
DOI :
10.1109/ICMLC.2009.5212244
