DocumentCode :
2526702
Title :
Research on an Algorithm of Support Vector Stepwise Regression
Author :
Zeng, Shaohua ; Wei, Yan ; Duan, Tingcai ; Cao, Changxiu
Author_Institution :
Coll. of Autom., Chongqing Univ.
Volume :
3
fYear :
2006
fDate :
Aug. 30 2006-Sept. 1 2006
Firstpage :
452
Lastpage :
458
Abstract :
SVM (support vector machine) is an important tool of solving the nonlinear problem. This paper introduces the methods of constructing support vector stepwise regression - starting from the multiple linear regression model of the sample subset to search the support vectors. It provides a speedy algorithm of support vector stepwise regression with the aim of decreasing the size of the kernel matrix and reducing the computing complexity of support vector stepwise regression, analyzes the complexity of the algorithm, and illustrates an application example
Keywords :
computational complexity; nonlinear equations; regression analysis; support vector machines; computational complexity; linear regression model; nonlinear problem; speedy algorithm; support vector machine; support vector stepwise regression; Algorithm design and analysis; Automation; Data mining; Educational institutions; Genetic algorithms; Kernel; Linear regression; Mathematics; Quadratic programming; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7695-2616-0
Type :
conf
DOI :
10.1109/ICICIC.2006.504
Filename :
1692211
Link To Document :
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