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Determining the Eps Parameter of the DBSCAN Algorithm

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Artificial Intelligence and Soft Computing (ICAISC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11509))

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Abstract

Clustering is an attractive technique used in many fields and lots of clustering algorithms have been proposed so far. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is one of the most popular algorithms, which has been widely applied in many different applications. This algorithm can discover clusters of arbitrary shapes in large datasets. However, the fundamental issue is the right choice of two input parameters, i.e. radius eps and density threshold MinPts. In this paper, a new method is proposed to determine the value of eps. The suggested approach is based on an analysis of the sorted values of the distance function. The performance of the new approach has been demonstrated for several different datasets.

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Author information

Authors and Affiliations

  1. Institute of Computational Intelligence, Częstochowa University of Technology, Al. Armii Krajowej 36, 42-200, Częstochowa, Poland

    Artur Starczewski

  2. Information Technology Institute, University of Social Sciences, 90-113, Łódź, Poland

    Andrzej Cader

  3. Clark University, Worcester, MA, 01610, USA

    Andrzej Cader

Authors
  1. Artur Starczewski
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  2. Andrzej Cader
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Corresponding author

Correspondence to Artur Starczewski .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

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

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Starczewski, A., Cader, A. (2019). Determining the Eps Parameter of the DBSCAN Algorithm. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2019. Lecture Notes in Computer Science(), vol 11509. Springer, Cham. https://doi.org/10.1007/978-3-030-20915-5_38

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  • DOI: https://doi.org/10.1007/978-3-030-20915-5_38

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20914-8

  • Online ISBN: 978-3-030-20915-5

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