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
Link To Document :
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