Using proximity and spatial homogeneity in neighbourhood-based classifiers

  • J. S. Sánchez
  • F. Pla
  • F. J. Ferri
Poster Session A: Color & Texture, Enhancement, Image Analysis & Pattern Recognition, Segmentation
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1310)


In this paper, a set of neighbourhood-based classifiers are jointly used in order to select a more reliable neighbourhood of a given sample and take an appropriate decision about its class membership. The approaches introduced here make use of two concepts: proximity and symmetric placement of the samples.


Classification Accuracy Single Classifier Pattern Recognition Letter Minimum Classification Error Multiple Classifier System 
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 1997

Authors and Affiliations

  • J. S. Sánchez
    • 1
  • F. Pla
    • 1
  • F. J. Ferri
    • 2
  1. 1.Departament d'InformàticaUniversitat Jaume ICastellóSpain
  2. 2.Departament d'Informàtica i ElectrónicaUniversitat de ValènciaBurjassot (València)Spain

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