Fuzzy labeled self-organizing map for classification of spectra

Authors:
T. Villmann;F.-M. Schleif;E. Merenyi;B. Hammer
Affiliations:
University Leipzig, Medical Department;University Leipzig, Medical Department;Rice University Houston;Clausthal University of Technology, Institute of Computer Science
Venue:
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
Year:
2007

Citing 7
Cited 1

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Fuzzy supervised self-organizing map for semi-supervised vector quantization

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Abstract

We extend the self-organizing map to a supervised fuzzy classification method. On the one hand, this leads to a robust classifier where efficient learning of fuzzy labeled or partially contradictory data is possible. On the other hand, class similarities may be detected. Further, we integrate the parametrized functional metric as data similarity measure into the approach. Parametrization of this functional metric allows relevance learning for efficient classification and feature selection.