Statistically---Induced kernel function for support vector machine classifier

Authors:
Cezary Dendek;Jacek Mańdziuk
Affiliations:
Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland;Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
Venue:
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Year:
2012

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Abstract

In this paper a new family of kernel functions for SVM classifiers, based on a statistically---induced measure of distance between observations in the pattern space, is proposed and experimentally evaluated in the context of binary classification problems. The application of the proposed approach improves the accuracy of results compared to the case of training without postulated enhancements. Numerical results outperform those of the SVM with Gaussian and Laplace kernels.