Similarity-based learning for pattern classification

Laurene V. Fausett

doi:10.1117/12.235944

22 March 1996 Similarity-based learning for pattern classification

Laurene V. Fausett

Proceedings Volume 2760, Applications and Science of Artificial Neural Networks II; (1996) https://doi.org/10.1117/12.235944
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

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.

Citation Download Citation

Laurene V. Fausett "Similarity-based learning for pattern classification", Proc. SPIE 2760, Applications and Science of Artificial Neural Networks II, (22 March 1996); https://doi.org/10.1117/12.235944

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