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International Conference: Beyond Databases, Architectures and Structures

BDAS 2017: Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation pp 89–101Cite as

Adjusting Parameters of the Classifiers in Multiclass Classification

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 716))

Abstract

The article presents the results of the optimization process of classification for five selected data sets. These data sets contain the data for the realization of the multiclass classification. The article presents the results of initial classification, carried out by dozens of classifiers, as well as the results after the process of adjusting parameters, this time obtained for a set of selected classifiers. At the end of article, a summary and the possibility of further work are provided.

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Acknowledgements

This work was partly supported by BKM16/RAU2/507 and BK-219/RAU2/2016 grants from the Institute of Informatics, Silesian University of Technology, Poland.

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Authors and Affiliations

  1. Silesian University of Technology, Gliwice, Poland

    Daniel Kostrzewa & Robert Brzeski

Authors
  1. Daniel Kostrzewa
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  2. Robert Brzeski
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Corresponding author

Correspondence to Daniel Kostrzewa .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Dariusz Mrozek

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Paweł Kasprowski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Bożena Małysiak-Mrozek

  5. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Daniel Kostrzewa

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Kostrzewa, D., Brzeski, R. (2017). Adjusting Parameters of the Classifiers in Multiclass Classification. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation. BDAS 2017. Communications in Computer and Information Science, vol 716. Springer, Cham. https://doi.org/10.1007/978-3-319-58274-0_8

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  • DOI: https://doi.org/10.1007/978-3-319-58274-0_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58273-3

  • Online ISBN: 978-3-319-58274-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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