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International Workshop on Multiple Classifier Systems

MCS 2003: Multiple Classifier Systems pp 326–335Cite as

New Boosting Algorithms for Classification Problems with Large Number of Classes Applied to a Handwritten Word Recognition Task

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2709))

Abstract

Methods that create several classifiers out of one base classifier, so-called ensemble creation methods, have been proposed and successfully applied to many classification problems recently. One category of such methods is Boosting with AdaBoost being the best known procedure belonging to this category. Boosting algorithms were first developed for two-class problems, but then extended to deal with multiple classes. Yet these extensions are not always suitable for problems with a large number of classes. In this paper we introduce some novel boosting algorithms which are designed for such problems, and we test their performance in a handwritten word recognition task.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Bern, Neubrückstrasse 10, CH-3012, Bern, Switzerland

    Simon Günter & Horst Bunke

Authors
  1. Simon Günter
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  2. Horst Bunke
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Editor information

Editors and Affiliations

  1. Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, Surrey, GU2 7XH, UK

    Terry Windeatt

  2. Dept. of Electrical and Electronic Engineering, University of Cagliari, Piazza D’Ami, 09123, Cagliari, Italy

    Fabio Roli

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© 2003 Springer-Verlag Berlin Heidelberg

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Günter, S., Bunke, H. (2003). New Boosting Algorithms for Classification Problems with Large Number of Classes Applied to a Handwritten Word Recognition Task. In: Windeatt, T., Roli, F. (eds) Multiple Classifier Systems. MCS 2003. Lecture Notes in Computer Science, vol 2709. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44938-8_33

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  • DOI: https://doi.org/10.1007/3-540-44938-8_33

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40369-2

  • Online ISBN: 978-3-540-44938-6

  • eBook Packages: Springer Book Archive

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