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Supervised Hybrid SOM-NG Algorithm

Authors:
Mario J. Crespo-Ramos
Ivan Machon-Gonzalez
Hilario Lopez-Garcia
Jose Luis Calvo-Rolle

Keywords: hybrid algorithm, supervised learning, neural networks, self-organizing mapping, neural gas

Abstract:
The hybrid SOM-NG algorithm was formulated to improve the quantization precision in Self Organizing Maps by the means of combine both SOM and Neural Gas properties using a parameter gamma to tune the topology preservation. A supervised learning algorithm is proposed to take advantage of the balanced hybrid algorithm. The proposed algorithm makes a linear approximation of the goal function for every Voronoi region. The algorithm gives good estimations and well balanced prototype positions combining the benefits of the original algorithms.

Pages: 113 to 118

Copyright: Copyright (c) IARIA, 2011

Publication date: November 20, 2011

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-172-4

Location: Lisbon, Portugal

Dates: from November 20, 2011 to November 25, 2011