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Clustering and Weighted Scoring Algorithm Based on Estimating the Number of Clusters

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Computational Science – ICCS 2021 (ICCS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12744))

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Abstract

Imbalanced datasets are still a big method challenge in data mining and machine learning. Various machine learning methods and their combinations are considered to improve the quality of the classification of imbalanced datasets. This paper presents the approach with the clustering and weighted scoring function based on geometric space are used. In particular, we proposed a significant modification to our earlier algorithm. The proposed change concerns the use of automatic estimating the number of clusters and determining the minimum number of objects in a particular cluster. The proposed algorithm was compared with our earlier proposal and state-of-the-art algorithms using highly imbalanced datasets. The performed experiments show that the proposed modification is statistically better for a larger number of reference classifiers than the original algorithm.

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Notes

  1. 1.

    Repository link: https://github.com/w4k2/cws-enc.

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Acknowledgements

This work was supported by the Polish National Science Centre under the grant No. 2017/25/B/ST6/01750 as well as by the statutory funds of the Department of Systems and Computer Networks, Faculty of Electronics, Wroclaw University of Science and Technology.

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Authors and Affiliations

  1. Department of Systems and Computer Networks, Wroclaw University of Science and Technology, Wroclaw, Poland

    Jakub Klikowski & Robert Burduk

Authors
  1. Jakub Klikowski
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  2. Robert Burduk
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Corresponding author

Correspondence to Robert Burduk .

Editor information

Editors and Affiliations

  1. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  2. Ludwig-Maximilians-Universität München, Munich, Germany

    Dieter Kranzlmüller

  3. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  4. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  5. University of Amsterdam, Amsterdam, The Netherlands

    Peter M.A. Sloot

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Klikowski, J., Burduk, R. (2021). Clustering and Weighted Scoring Algorithm Based on Estimating the Number of Clusters. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12744. Springer, Cham. https://doi.org/10.1007/978-3-030-77967-2_4

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  • DOI: https://doi.org/10.1007/978-3-030-77967-2_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77966-5

  • Online ISBN: 978-3-030-77967-2

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