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NCA
2008
IEEE

Polynomial kernel adaptation and extensions to the SVM classifier learning

13 years 5 months ago
Polynomial kernel adaptation and extensions to the SVM classifier learning
Three extensions to the Kernel-AdaTron training algorithm for Support Vector Machine classifier learning are presented. These extensions allow the trained classifier to adhere more closely to the constraints imposed by Support Vector Machine theory. The results of these modifications show improvements over the existing Kernel-AdaTron algorithm. A method of parameter optimisation for polynomial kernels is also proposed. Keywords Kernel methods
Ramy Saad, Saman K. Halgamuge, Jason Li
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2008
Where NCA
Authors Ramy Saad, Saman K. Halgamuge, Jason Li
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