DocumentCode :
3491323
Title :
Multi-class support vector machines: a new approach
Author :
Arenas-Garcia, Jerónimo ; Pérez-Cruz, Fernando
Author_Institution :
Dept. of Signal Theor. & Commun., Univ. Carlos III, Madrid, Spain
Volume :
2
fYear :
2003
fDate :
6-10 April 2003
Abstract :
We propose a new approach for solving multiclass problems with support vector machines. We modify the existing technique to properly reduce the empirical error, therefore we will be ideally able to outperform the previously proposed scheme for multi-class SVMs. The proposed approach also provides solutions with a significant reduction in the number of support vectors, which is an important feature for fast systems.
Keywords :
learning automata; signal classification; statistical analysis; binary classification SVM; classification error; fast systems; multi-class SVM; multi-class support vector machines; optimization; quadratic programming; statistical learning theory; training time; Support vector machine classification; Support vector machines; Voting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-7663-3
Type :
conf
DOI :
10.1109/ICASSP.2003.1202483
Filename :
1202483
Link To Document :
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