Visualization of high-dimensional data using two-dimensional self-organizing piecewise-smooth Kohonen maps

Authors:
A. V. Shklovets;N. G. Axak
Affiliations:
Kharkov National Radioelectronics University, Kharkov, Ukraine;Kharkov National Radioelectronics University, Kharkov, Ukraine
Venue:
Optical Memory and Neural Networks
Year:
2012

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Abstract

To make visualization of high-dimensional data more accurate, we offer a method of approximating two-dimensional Kohonen maps lying in a multiple-dimensional space. Cubic parametric spline-based least-defect surfaces can be used as an approximation function to minimize approximation errors.