Fast Multistage Algorithm for K-NN Classifiers

  • I. Soraluze
  • C. Rodriguez
  • F. Boto
  • A. Cortes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2905)

Abstract

In this paper we present a way to reduce the computational cost of k-NN classifiers without losing classification power. Hierarchical or multistage classifiers have been built with this purpose. These classifiers are designed putting incrementally trained classifiers into a hierarchy and using rejection techniques in all the levels of the hierarchy apart from the last. Results are presented for different benchmark data sets: some standard data sets taken from the UCI Repository and the Statlog Project, and NIST Special Databases (digits and upper-case and lower-case letters). In all the cases a computational cost reduction is obtained maintaining the recognition rate of the best individual classifier obtained.

Keywords

Recognition Rate Near Neighbor Good Recognition Rate Multistage Classifier Handwritten Digit Recognition 
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 2003

Authors and Affiliations

  • I. Soraluze
    • 1
  • C. Rodriguez
    • 1
  • F. Boto
    • 1
  • A. Cortes
    • 1
  1. 1.Computer Architecture and Technology DepartmentComputer Science Faculty, UPV/EHUSan SebastianSpain

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