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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2016: Artificial Intelligence and Soft Computing pp 114–124Cite as

A Modification of the Silhouette Index for the Improvement of Cluster Validity Assessment

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9693))

Abstract

In this paper a modification of the well-known Silhouette validity index is proposed. This index, which can be considered a measure of the data set partitioning accuracy, enjoys significant popularity and is often used by researchers. The proposed modification involves using an additional component in the original index. This approach improves performance of the index and provides better results during a clustering process, especially when changes of cluster separability are big. The new version of the index is called the SILA index and its maximum value identifies the best clustering scheme. The performance of the new index is demonstrated for several data sets, where the popular algorithm has been applied as underlying clustering techniques, namely the Complete–linkage algorithm. The results prove superiority of the new approach as compared to the original Silhouette validity index.

A. Krzyżak carried out this research at WUT during his sabbatical leave from Concordia University.

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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. Department of Computer Science and Software Engineering, Concordia University, Montreal, Canada

    Adam Krzyżak

  3. Department of Electrical Engineering, Westpomeranian University of Technology, 70-313, Szczecin, Poland

    Adam Krzyżak

Authors
  1. Artur Starczewski
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  2. Adam Krzyżak
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Corresponding author

Correspondence to Artur Starczewski .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Czestochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Czestochowa, Poland

    Marcin Korytkowski

  3. Częstochowa University of Technology, Czestochowa, Poland

    Rafał Scherer

  4. AGH University of Science and Technology, Krakow, 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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Starczewski, A., Krzyżak, A. (2016). A Modification of the Silhouette Index for the Improvement of Cluster Validity Assessment. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2016. Lecture Notes in Computer Science(), vol 9693. Springer, Cham. https://doi.org/10.1007/978-3-319-39384-1_10

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  • DOI: https://doi.org/10.1007/978-3-319-39384-1_10

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  • Publisher Name: Springer, Cham

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