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Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes

  • Thomas Villmann
  • Udo Seiffert
  • Frank-Michael Schleif
  • Cornelia Brüß
  • Tina Geweniger
  • Barbara Hammer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4087)

Abstract

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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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Thomas Villmann
    • 1
  • Udo Seiffert
    • 2
  • Frank-Michael Schleif
    • 3
    • 4
  • Cornelia Brüß
    • 2
  • Tina Geweniger
    • 4
    • 5
  • Barbara Hammer
    • 6
  1. 1.Medical DepartmentUniversity Leipzig 
  2. 2.IPK Gatersleben, Pattern Recognition Group 
  3. 3.BRUKER Daltonik Leipzig, Numerical Toolbox Group 
  4. 4.Institute of Computer ScienceUniversity Leipzig 
  5. 5.Computer ScienceUniversity of Applied Science Mittweida 
  6. 6.Institute of Computer ScienceClausthal University of Technology 

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