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A New Clustering Preserving Transformation for k-Means Algorithm Output

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Foundations of Intelligent Systems (ISMIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13515))

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Abstract

A novel clustering preserving transformation of cluster sets obtained from k-means algorithm is introduced. This transformation may be used to generate new labeled datasets from existent ones. It is more flexible than Kleinberg axiom based consistency transformation because data points in a cluster can be moved away and datapoints between clusters may come closer together.

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Authors and Affiliations

  1. Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland

    Mieczysław A. Kłopotek

Authors
  1. Mieczysław A. Kłopotek
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Correspondence to Mieczysław A. Kłopotek .

Editor information

Editors and Affiliations

  1. Università degli Studi di Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

  2. Università della Calabria, Rende, Italy

    Sergio Flesca

  3. Università Federico II di Napoli, Naples, Italy

    Elio Masciari

  4. ICAR-CNR, Rende, Italy

    Giuseppe Manco

  5. University of North Carolina, Charlotte, NC, USA

    Zbigniew W. Raś

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Kłopotek, M.A. (2022). A New Clustering Preserving Transformation for k-Means Algorithm Output. In: Ceci, M., Flesca, S., Masciari, E., Manco, G., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2022. Lecture Notes in Computer Science(), vol 13515. Springer, Cham. https://doi.org/10.1007/978-3-031-16564-1_30

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  • DOI: https://doi.org/10.1007/978-3-031-16564-1_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16563-4

  • Online ISBN: 978-3-031-16564-1

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