Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes

We extend the self-organizing map (SOM) in the form as proposed by Heskes to a supervised fuzzy classification method. On the one hand, this leads to a robust classifier where efficient learning with fuzzy labeled or partially contradictory data is possible. On the other hand, the integration of lab...

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Hauptverfasser: Villmann, Thomas, Seiffert, Udo, Schleif, Frank-Michael, Brüß, Cornelia, Geweniger, Tina, Hammer, Barbara
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Seiffert, Udo
Schleif, Frank-Michael
Brüß, Cornelia
Geweniger, Tina
Hammer, Barbara
description We extend the self-organizing map (SOM) in the form as proposed by Heskes to a supervised fuzzy classification method. On the one hand, this leads to a robust classifier where efficient learning with fuzzy labeled or partially contradictory data is possible. On the other hand, the integration of labeling into the location of prototypes in a SOM leads to a visualization of those parts of the data relevant for the classification.
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subjects Applied sciences
Artificial intelligence
Computer science
control theory
systems
Connectionism. Neural networks
Exact sciences and technology
title Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes
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