A Supervised Self-Organizing Map for Structured Data

  • Markus Hagenbuchner
  • Ah Chung Tsoi
  • Alessandro Sperduti


A self organizing map (SOM) for processing of structured data, using an unsupervised learning approach, called SOM-SD, has recently been proposed. Here, we suggest a new version of SOM, using the supervised learning approach. We compare the supervised version and the unsupervised version of SOM-SD on a benchmark problem involving visual patterns. As may be expected, the supervised version is able to solve the classification problem using very compact networks.


Root Node Leaf Node Directed Acyclic Graph Target Class Winning Neuron 
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Copyright information

© Springer-Verlag London Limited 2001

Authors and Affiliations

  • Markus Hagenbuchner
    • 1
  • Ah Chung Tsoi
    • 1
  • Alessandro Sperduti
    • 2
  1. 1.Faculty of InformaticsUniversity of WollongongAustralia
  2. 2.Dip. di InformaticaUniversità di PisaPisaItaly

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