'Periodica Polytechnica Budapest University of Technology and Economics'
Abstract
In this tutorial type paper a Mathematica function for Support Vector Regression has
been developed. Summarizing the main definitions and theorems of SVR, the
detailed implementation steps of this function are presented and its
application is illustrated by solving three 2D function approximation test
problems, employing a stronger regularized universal Fourier and a wavelet
kernel. In addition, a real world regression problem, forecasting of the peak
of flood-wave is also solved. The %numeric and symbolic
results show how
easily and effectively Mathematica can be used for solving SVR problems