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Fuzzy Clustering with \(\varepsilon \)-Hyperballs and Its Application to Data Classification

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Artificial Intelligence and Soft Computing (ICAISC 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10246))

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Abstract

In the presented paper the Fuzzy Clustering with \(\varepsilon \)-Hyperballs being the prototypes is proposed. It is based on the idea of regions of insensitivity – described by the hyperballs of radius \(\varepsilon \), in which the distances of objects from the centers of the hyperballs are considered as equal to zero. The proposed clustering was applied to determine the parameters of fuzzy sets in antecedents of the classifier based on fuzzy if-then rules. The classification quality obtained for six benchmark datasets was compared with the reference classifiers. The results show the improvement of the classification accuracy using the proposed method.

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Acknowledgments

This work was partially supported by the Ministry of Science and Higher Education funding for: statutory activities of young researchers (BKM-508/RAu-3/2016) and statutory activities (BK-220/RAu-3/2016).

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Authors and Affiliations

  1. Faculty of Automatic Control, Electronics and Computer Science, Institute of Electronics, Silesian University of Technology, 16 Akademicka Str., 44-100, Gliwice, Poland

    Michal Jezewski, Robert Czabanski & Jacek Leski

Authors
  1. Michal Jezewski
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  2. Robert Czabanski
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  3. Jacek Leski
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Corresponding author

Correspondence to Michal Jezewski .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  5. University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  6. University of Louisville, Louisville, Kentucky, USA

    Jacek M. Zurada

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Jezewski, M., Czabanski, R., Leski, J. (2017). Fuzzy Clustering with \(\varepsilon \)-Hyperballs and Its Application to Data Classification. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2017. Lecture Notes in Computer Science(), vol 10246. Springer, Cham. https://doi.org/10.1007/978-3-319-59060-8_9

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  • DOI: https://doi.org/10.1007/978-3-319-59060-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59059-2

  • Online ISBN: 978-3-319-59060-8

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