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International Conference on Computer Recognition Systems

CORES 2019: Progress in Computer Recognition Systems pp 360–369Cite as

Multi Sampling Random Subspace Ensemble for Imbalanced Data Stream Classification

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 977))

Abstract

The classification of data streams is a frequently considered problem. The data coming in over time has a tendency to change its characteristics over time and usually we also encounter some difficulties in data distributions as inequality of the number of learning examples from considered classes. The combination of these two phenomena is an additional challenge. In this article, we propose a novel MSRS (Multi Sampling Random Subspace Ensemble) a chunk-based ensemble method for imbalanced non-stationary data stream classification. The proposed algorithm employs random subspace approach and balancing data using various sampling methods to ensure an appropriate diversity of the classifier ensemble. MSRS has been evaluated on the basis of the computer experiments carried out on the diverse pool of the non-stationary imbalanced data streams.

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Notes

  1. 1.

    https://github.com/JakubKlik/msrs.

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Acknowledgement

This work was supported by the Polish National Science Centre under the grant No. 2017/27/B/ST6/01325.

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Authors and Affiliations

  1. Wrocław University of Science and Technology, Wrocław, Poland

    Jakub Klikowski & Michał Woźniak

Authors
  1. Jakub Klikowski
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  2. Michał Woźniak
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Corresponding authors

Correspondence to Jakub Klikowski or Michał Woźniak .

Editor information

Editors and Affiliations

  1. Faculty of Electronics, Wroclaw University of Science and Technology, Wrocław, Poland

    Robert Burduk

  2. Faculty of Electronics, Wroclaw University of Science and Technology, Wrocław, Poland

    Marek Kurzynski

  3. Faculty of Electronics, Wroclaw University of Science and Technology, Wrocław, Poland

    Michał Wozniak

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Klikowski, J., Woźniak, M. (2020). Multi Sampling Random Subspace Ensemble for Imbalanced Data Stream Classification. In: Burduk, R., Kurzynski, M., Wozniak, M. (eds) Progress in Computer Recognition Systems. CORES 2019. Advances in Intelligent Systems and Computing, vol 977. Springer, Cham. https://doi.org/10.1007/978-3-030-19738-4_36

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