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

Authors:
Milton García-Borroto;Yenny Villuendas-Rey;Jesús Ariel Carrasco-Ochoa;José Fco. Martínez-Trinidad
Affiliations:
Bioplantas Center, UNICA, C. de Ávila, Cuba and National Institute of Astrophysics, Optics and Electronics, Puebla, México;Ciego de Ávila University UNICA, C. de Ávila, Cuba;National Institute of Astrophysics, Optics and Electronics, Puebla, México;National Institute of Astrophysics, Optics and Electronics, Puebla, México
Venue:
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Year:
2009

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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.