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Finding Small Consistent Subset for the Nearest Neighbor Classifier Based on Support Graphs

  • Milton García-Borroto
  • Yenny Villuendas-Rey
  • Jesús Ariel Carrasco-Ochoa
  • José Fco. Martínez-Trinidad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5856)

Abstract

Finding a minimal subset of objects that correctly classify the training set for the nearest neighbors classifier has been an active research area in Pattern Recognition and Machine Learning communities for decades. Although finding the Minimal Consistent Subset is not feasible in many real applications, several authors have proposed methods to find small consistent subsets. In this paper, we introduce a novel algorithm for this task, based on support graphs. Experiments over a wide range of repository databases show that our algorithm finds consistent subsets with lower cardinality than traditional methods.

Keywords

nearest neighbor condensing prototype selection minimal consistent subset 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Milton García-Borroto
    • 1
    • 3
  • Yenny Villuendas-Rey
    • 2
  • Jesús Ariel Carrasco-Ochoa
    • 3
  • José Fco. Martínez-Trinidad
    • 3
  1. 1.Bioplantas CenterUNICAC. de ÁvilaCuba
  2. 2.Ciego de Ávila University UNICAC. de ÁvilaCuba
  3. 3.National Institute of Astrophysics, Optics and ElectronicsPueblaMéxico

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