Konferensartikel

Supervised SOM Based Architecture versus Multilayer Perceptron and RBF Networks

David Gil
Computing Technology and Data Processing, University of Alicante, Spain

Magnus Johnsson
Lund University Cognitive Science, Lund, Sweden

Ladda ner artikelhttp://www.ep.liu.se/ecp_article/index.en.aspx?issue=048;article=005

Ingår i: The Swedish AI Society Workshop May 20-21; 2010; Uppsala University

Linköping Electronic Conference Proceedings 48:5, s. 15-24

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Publicerad: 2010-05-19

ISBN:

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

We address a contrastive study between the well known Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) neural networks and a SOM based supervised architecture in a number of data classification tasks. Well known databases like Breast Cancer; Parkinson and Iris were used to evaluate the three architectures by constructing confusion matrices. The results are encouraging and indicate that the SOM based supervised architecture generally achieves results as good as the MLP and slightly higher on some measures than the RBF network.

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