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New Data Level Approach for Imbalanced Data Classification Improvement

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Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

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

Abstract

The article concerns the problem of imbalanced data classification. The algorithm improving a standard SMOTE method has been proposed and tested. It is a synergy of the existing approaches and was designed to be more versatile than other similar solutions. To measure the distance between objects, the Euclidean or the HVDM metrics were applied, depending on the number of nominal attributes in a data set.

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References

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Author information

Authors and Affiliations

  1. Faculty of Computer Science, Bialystok University of Technology, Bialystok, Poland

    Katarzyna Borowska & Magdalena Topczewska

Authors
  1. Katarzyna Borowska
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  2. Magdalena Topczewska
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Corresponding author

Correspondence to Magdalena Topczewska .

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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© 2016 Springer International Publishing Switzerland

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Borowska, K., Topczewska, M. (2016). New Data Level Approach for Imbalanced Data Classification Improvement. 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_27

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  • DOI: https://doi.org/10.1007/978-3-319-26227-7_27

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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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