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Learning in Pattern Recognition

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Machine Learning and Data Mining in Pattern Recognition (MLDM 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1715))

Abstract

Learning in the context of a pattern recognition system is defined as the process that allows it to cope with real and ambiguous data. The various ways by which artificial decision systems operate are discussed in conjunction with their learning aspects.

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References

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Author information

Authors and Affiliations

  1. School of Electronic Engineering, Information Technology and Mathematics, University of Surrey, Guildford, GU2 5XH, UK

    M. Petrou

Authors
  1. M. Petrou
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Editor information

Editors and Affiliations

  1. Institut für Bildverarbeitung und angewandte Informatik, Arno-Nitzsche-Str. 45, D-04277, Leipzig, Germany

    Petra Perner

  2. School of Electronic Engineering, Information Technology and Mathematics, University of Surrey, Guilford, GU2 5XH, UK

    Maria Petrou

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© 1999 Springer-Verlag Berlin Heidelberg

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Petrou, M. (1999). Learning in Pattern Recognition. In: Perner, P., Petrou, M. (eds) Machine Learning and Data Mining in Pattern Recognition. MLDM 1999. Lecture Notes in Computer Science(), vol 1715. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48097-8_1

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  • DOI: https://doi.org/10.1007/3-540-48097-8_1

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66599-1

  • Online ISBN: 978-3-540-48097-6

  • eBook Packages: Springer Book Archive

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