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Analyzing Classifier Hierarchy Multiclassifier Learning

  • J. M. Martínez-Otzeta
  • B. Sierra
  • E. Lazkano
  • E. Jauregi
  • Y. Yurramendi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)

Abstract

Classifier combination falls in the so called machine learning area. Its aim is to combine some classification paradigms in order to improve the individual accuracy of the component classifiers. Classifier hierarchies are an alternative among the several methods of classifier combination. In this paper we present new results about a recently proposed hierarchy construction method. Experiments have been carried out over 42 databases from the UCI repository, showing an improvement over the performance of the base classifiers.

Keywords

Classifier combination hierarchy of classifiers data mining 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • J. M. Martínez-Otzeta
    • 1
  • B. Sierra
    • 2
  • E. Lazkano
    • 2
  • E. Jauregi
    • 2
  • Y. Yurramendi
    • 2
  1. 1.Fundación TeknikerEibarSpain
  2. 2.Department of Computer Science and Artificial IntelligenceUniversity of the Basque CountryDonostia-San SebastiánSpain

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