Topographic Measure Based on External Criteria for Self-Organizing Map

  • Ken-ichi Fukui
  • Masayuki Numao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6731)


We proposed the methodology of introducing topographic component to conventional clustering measures for the evaluation of the SOM using external criteria, i.e., class information. The topographic measure evaluates clustering accuracy together with topographic connectivity of class distribution on the topology space of the SOM. The topographic component is introduced by marginalization of basic statistics to the set-based measures, and by a likelihood function to the pairwise-based measures. Our method can extend any clustering measure based on set or pairwise of data points. The present paper examined the topographic component of the extended measure and revealed an appropriate neighborhood radius of the topographic measures.


clustering measure topology neighborhood function 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ken-ichi Fukui
    • 1
  • Masayuki Numao
    • 1
  1. 1.The Institute of Scientific and Industrial Research (ISIR)Osaka UniversityIbarakiJapan

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