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- W2386532351 abstract "Support Vector Machines(SVMs) a new way based on statistical theory,was proposed by Vapnik.It has been well studied and widely applied to the classification and regression.According to the Structural Risk Minimization(SRM) principle,SVM has a better performance on generalization contrast than classic methods.The choice of kernel function of SVM is key factor in the performance.In this paper,Fourier kernel is studied.A conclusion is drawn that,in some area,SVM based on Fourier kernel is better than that based on RBF kernel.At last,a simulation is conducted to illustrate it." @default.
- W2386532351 created "2016-06-24" @default.
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- W2386532351 date "2005-01-01" @default.
- W2386532351 modified "2023-09-23" @default.
- W2386532351 title "A performance comparison of SVMs based on Fourier kernel and RBF kernel" @default.
- W2386532351 hasPublicationYear "2005" @default.
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