DocumentCode :
3417982
Title :
A Simplification to Support Vector Machine for the Second Training
Author :
Fang, Jinglong ; Chen, Shuo ; Pan, Zhigeng ; Wang, Yigang
Author_Institution :
Inst. of Graphics & Image, Hangzhou Dianzi Univ., Hangzhou
fYear :
2006
fDate :
Nov. 29 2006-Dec. 1 2006
Firstpage :
73
Lastpage :
78
Abstract :
For complicated recognition problem, the number of support vectors is large and recognition speed is low, because some sample were divided into section by error this time. To solve this problem, a method is bought to simplify the support vector machines based the minimal misestimate margin idea. Experiments show that this new support vector machine not only reduces the number of support vectors and recognition time but also has the same accuracy as (even better than) traditional support vector machine.
Keywords :
pattern recognition; support vector machines; complicated recognition problem; machine learning; recognition speed; support vector machine; Classification algorithms; Graphics; Image analysis; Image classification; Laboratories; Machine learning; Standards development; Support vector machine classification; Support vector machines; Valves;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Artificial Reality and Telexistence--Workshops, 2006. ICAT '06. 16th International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
0-7695-2754-X
Type :
conf
DOI :
10.1109/ICAT.2006.27
Filename :
4089214
Link To Document :
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