Polynomial kernel adaptation and extensions to the SVM classifier learning

Saad, Ramy; Halgamuge, Saman K.; Li, Jason

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Polynomial kernel adaptation and extensions to the SVM classifier learning

Date

2008

Authors

Saad, Ramy

Halgamuge, Saman K.

Li, Jason

Abstract

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.