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