Mp-polynomial kernel for training support vector machines
I Mejía-Guevara, Á Kuri-Morales - … November 13-16, 2007. Proceedings 12, 2007 - Springer
Progress in Pattern Recognition, Image Analysis and Applications: 12th …, 2007•Springer
In this article we present a new polynomial function that can be used as a kernel for Support
Vector Machines (SVMs) in binary classification and regression problems. We prove that this
function fulfills the mathematical properties of a kernel. We consider here a set of SVMs
based on this kernel with which we perform a set of experiments. Their efficiency is
measured against some of the most popular kernel functions reported in the past.
Vector Machines (SVMs) in binary classification and regression problems. We prove that this
function fulfills the mathematical properties of a kernel. We consider here a set of SVMs
based on this kernel with which we perform a set of experiments. Their efficiency is
measured against some of the most popular kernel functions reported in the past.
Abstract
In this article we present a new polynomial function that can be used as a kernel for Support Vector Machines (SVMs) in binary classification and regression problems. We prove that this function fulfills the mathematical properties of a kernel. We consider here a set of SVMs based on this kernel with which we perform a set of experiments. Their efficiency is measured against some of the most popular kernel functions reported in the past.
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