DocumentCode
1949383
Title
Research on Combination Kernel Function of Support Vector Machine
Author
Song, Huazhu ; Ding, Zichun ; Guo, Cuicui ; Li, Zhe ; Xia, Hongxia
Author_Institution
Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan
Volume
1
fYear
2008
fDate
12-14 Dec. 2008
Firstpage
838
Lastpage
841
Abstract
The kernel function and parameters selection is a key problem in the research of support vector machine. After discussing the influence of support vector machine on kernel parameters and error penalty factors, a new kernel function CombKer was proposed and constructed. The CombKer kernel function is a kind of combination kernel function, which combines the Gaussian RBF kernel function that has the local characteristic, with the linear kernel function that has the global characteristic. Finally, some experiments on different domains data in the support vector machine constructed by the CombKer kernel function were done, and the results showed the better ability on prediction of this kind of support vector machine and proved the validation of the CombKer kernel function.
Keywords
Gaussian processes; radial basis function networks; support vector machines; CombKer combination kernel function; Gaussian RBF kernel function; error penalty factor; linear kernel function; parameter selection; support vector machine; Computer science; Kernel; Machine learning; Neural networks; Pattern analysis; Polynomials; Support vector machine classification; Support vector machines; Time series analysis; Virtual colonoscopy; Gaussian radial basis kernel function (RBF); Support Vector Machine (SVM); combination kernel function; linear kernel function;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location
Wuhan, Hubei
Print_ISBN
978-0-7695-3336-0
Type
conf
DOI
10.1109/CSSE.2008.1231
Filename
4721880
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