Influence of learning rates and neighboring functions on self-organizing maps

Authors:
Pavel Stefanović;Olga Kurasova
Affiliations:
Vilnius University, Institute of Mathematics and Informatics, Vilnius, Lithuania;Vilnius University, Institute of Mathematics and Informatics, Vilnius, Lithuania
Venue:
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
Year:
2011

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Abstract

In the article, the influence of neighboring functions and learning rates on self-organizing maps (SOM) has been investigated. The target of a selforganizing map is data clustering and their graphical presentation. Bubble, Gaussian, and heuristic neighboring functions and four learning rates (linear, inverse-of-time, power series, and heuristics) have been analyzed here. The learning rate has been changed according to epochs and iterations. A comparative analysis has been made with three data sets: glass, wine, and zoo. The quantization error has been measured in order to estimate the SOM quality.