Article | The Swedish AI Society Workshop May 20-21; 2010; Uppsala University | Supervised SOM Based Architecture versus Multilayer Perceptron and RBF Networks

Title:
Supervised SOM Based Architecture versus Multilayer Perceptron and RBF Networks
Author:
David Gil: Computing Technology and Data Processing, University of Alicante, Spain Magnus Johnsson: Lund University Cognitive Science, Lund, Sweden
Download:
Full text (pdf)
Year:
2010
Conference:
The Swedish AI Society Workshop May 20-21; 2010; Uppsala University
Issue:
048
Article no.:
005
Pages:
15-24
No. of pages:
10
Publication type:
Abstract and Fulltext
Published:
2010-05-19
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press; Linköpings universitet


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.

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

Author:
David Gil, Magnus Johnsson
Title:
Supervised SOM Based Architecture versus Multilayer Perceptron and RBF Networks
References:

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

Author:
David Gil, Magnus Johnsson
Title:
Supervised SOM Based Architecture versus Multilayer Perceptron and RBF Networks
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