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
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