DocumentCode
2496615
Title
A speedy model parameter optimization algorithm of support vector machines
Author
Chen, Zengzhao ; Liu, Chungui ; Yang, Yang ; He, Xiuling ; Don, Cailin
Author_Institution
Math. & Stat. Sch., Central China Normal Univ., Wuhan
fYear
2008
fDate
25-27 June 2008
Firstpage
7362
Lastpage
7367
Abstract
A speedy parameter optimization algorithm of SVM model is proposed. The algorithm selects a subset from the original training set, and optimizes respectively to ensure the bound of the parameters , then searches the optimum in the smaller range. Experiment shows that optimization of SVM parameters is more speedy and the accuracy is guaranteed in optimizing result.
Keywords
learning (artificial intelligence); optimisation; search problems; set theory; support vector machines; search problem; speedy parameter optimization algorithm; subset theory; support vector machine model; Automation; Character recognition; Electronic mail; Intelligent control; Mathematical model; Mathematics; Noise measurement; Research and development; Statistics; Support vector machines; Chinese character recognition; model parameter optimization; support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location
Chongqing
Print_ISBN
978-1-4244-2113-8
Electronic_ISBN
978-1-4244-2114-5
Type
conf
DOI
10.1109/WCICA.2008.4594064
Filename
4594064
Link To Document