ViSOM Ensembles for Visualization and Classification

  • Bruno Baruque
  • Emilio Corchado
  • Hujun Yin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4507)


In this paper ensemble techniques have been applied in the frame of topology preserving mappings in two applications: classification and visualization. These techniques are applied for the first time to the ViSOM and their performance is compared with ensemble combination of some other topology preserving mapping such as the SOM or the MLSIM. Several methods to obtain a meaningful combination of the components of an ensemble are presented and tested together with the existing ones in order to identify the best performing method in the applications of these models.


Classification Accuracy Input Space Competitive Learning Ensemble Technique Classification Capability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Bruno Baruque
    • 1
  • Emilio Corchado
    • 1
  • Hujun Yin
    • 2
  1. 1.Department of Civil Engineering. University of BurgosSpain
  2. 2.School of Electrical and Electronic Engineering. University of ManchesterUK

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