Towards Cluster-Based Prototype Sets for Classification in the Dissimilarity Space

  • Yenisel Plasencia-Calaña
  • Mauricio Orozco-Alzate
  • Edel García-Reyes
  • Robert P. W. Duin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8258)


The selection of prototypes for the dissimilarity space is a key aspect to overcome problems related to the curse of dimensionality and computational burden. How to properly define and select the prototypes is still an open issue. In this paper, we propose the selection of clusters as prototypes to create low-dimensional spaces. Experimental results show that the proposed approach is useful in the problems presented. Especially, the use of the minimum distances to clusters for representation provides good results.


dissimilarity space prototype selection cluster-based prototypes 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yenisel Plasencia-Calaña
    • 1
    • 2
  • Mauricio Orozco-Alzate
    • 3
  • Edel García-Reyes
    • 1
  • Robert P. W. Duin
    • 2
  1. 1.Advanced Technologies Application Center.PlayaCuba
  2. 2.Faculty of Electrical Engineering, Mathematics and Computer SciencesDelft University of TechnologyThe Netherlands
  3. 3.Departamento de Informática y ComputaciónUniversidad Nacional de ColombiaManizalesColombia

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