David Gil
Computing Technology and Data Processing, University of Alicante, Spain
Magnus Johnsson
Lund University Cognitive Science, Lund, Sweden
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Published in: The Swedish AI Society Workshop May 20-21; 2010; Uppsala University
Linköping Electronic Conference Proceedings 48:5, p. 15-24
Published: 2010-05-19
ISBN:
ISSN: 1650-3686 (print), 1650-3740 (online)
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.