Increasing the Number of Classifiers in Multi-classifier Systems: A Complementarity-Based Analysis

  • L. Bovino
  • G. Dimauro
  • S. Impedovo
  • G. Pirlo
  • A. Salzo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2423)


Complementarity among classifiers is a crucial aspect in classifier combination. A combined classifier is significantly superior to the individual classifiers only if they strongly complement each other. In this paper a complementarity-based analysis of sets of classifier is proposed for investigating the behaviour of multi-classifier systems, as new classifiers are added to the set. The experimental results confirm the theoretical evidence and allow the prediction of the performance of a multi-classifier system, as the number of classifiers increases.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • L. Bovino
    • 2
  • G. Dimauro
    • 1
  • S. Impedovo
    • 1
  • G. Pirlo
    • 1
  • A. Salzo
    • 2
  1. 1.Dipartimento di InformaticaUniversità degli Studi di BariBariItaly
  2. 2.Consorzio Interuniversitario Nazionale per l’Informatica (CINI)BariItaly

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