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Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015 pp 275–282Cite as

Comparison of Multi-label and Multi-perspective Classifiers in Multi-task Pattern Recognition Problems

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 403))

Abstract

This paper deals with the comparison of two different approaches for multi-task pattern recognition problem—multi-label and multi-perspective. The experiment performed measured the hamming loss and mean accuracy of both classifiers, to judge which of these two better fit to this kind of problem.

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References

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Author information

Authors and Affiliations

  1. Wroclaw University of Technology, Department of Systems and Computer Networks, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Edward Puchała & Krzysztof Reisner

Authors
  1. Edward Puchała
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  2. Krzysztof Reisner
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Corresponding author

Correspondence to Edward Puchała .

Editor information

Editors and Affiliations

  1. Department of Systems, Wrocław University of Technology, Wroclaw, Poland

    Robert Burduk

  2. Department of Systems and Computer, Wrocław University of Technology, Wroclaw, Poland

    Konrad Jackowski

  3. Department of Systems and Computer, Wrocław University of Technology, Wroclaw, Poland

    Marek Kurzyński

  4. Dept. of Systems and Computer Networks, Wrocław University of Technology, Wroclaw, Poland

    Michał Woźniak

  5. Department of Systems, Wrocław University of Technology, Wroclaw, Poland

    Andrzej Żołnierek

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Puchała, E., Reisner, K. (2016). Comparison of Multi-label and Multi-perspective Classifiers in Multi-task Pattern Recognition Problems. In: Burduk, R., Jackowski, K., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015. Advances in Intelligent Systems and Computing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-319-26227-7_26

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  • DOI: https://doi.org/10.1007/978-3-319-26227-7_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26225-3

  • Online ISBN: 978-3-319-26227-7

  • eBook Packages: EngineeringEngineering (R0)

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