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Proceedings Paper

Similarity-based learning for pattern classification
Author(s): Laurene V. Fausett
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Paper Abstract

Several standard neural networks, including counterpropagation networks, predictive ART networks, and radial basis function networks, are based on a combination of clustering (unsupervised learning) and mapping (supervised learning). A comparison of the characteristics of these networks for pattern classification problems is presented.

Paper Details

Date Published: 22 March 1996
PDF: 10 pages
Proc. SPIE 2760, Applications and Science of Artificial Neural Networks II, (22 March 1996); doi: 10.1117/12.235944
Show Author Affiliations
Laurene V. Fausett, Florida Institute of Technology (United States)

Published in SPIE Proceedings Vol. 2760:
Applications and Science of Artificial Neural Networks II
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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