DocumentCode
384410
Title
Speeding up SVM decision based on mirror points
Author
Chen, Jiun-Hung ; Chen, Chu-Song
Author_Institution
Inst. of Inf. Sci., Acad. Sinica, Taipei, Taiwan
Volume
2
fYear
2002
fDate
2002
Firstpage
869
Abstract
In this paper, we propose a new method to speed up SVM decision based on the idea of mirror points. Decisions based on multiple simple classifiers, which are formed as a result of mirror pairs, are combined to approximate a single SVM. A dynamic programming-based method is used to find a suitable combination. Experimental results show that this method can increase classification efficiencies of SVM with comparable classification performances.
Keywords
dynamic programming; image classification; learning automata; SVM decision speedup; classification efficiencies; dynamic programming based method; mirror points; multiple simple classifiers; Dynamic programming; Euclidean distance; Information science; Kernel; Mirrors; Polynomials; Quadratic programming; Support vector machine classification; Support vector machines; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2002. Proceedings. 16th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-1695-X
Type
conf
DOI
10.1109/ICPR.2002.1048440
Filename
1048440
Link To Document