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Retracted Article: A New Cluster Validity Index for Fuzzy Clustering Based on Similarity Measure

  • Conference paper
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4482))

Abstract

In this paper, first, the main problems of some cluster validity indices when they have been applied to Gustafson and Kessel (GK) clustering approach are review. It is shown that most of these cluster validity indices have serious shortcomings to validate Gustafson Kessel algorithm. Then, a new cluster validity index based on a similarity measure of fuzzy clusters for validation of GK algorithm is presented. This new index is not based on a geometric distance and can determine the degree of correlation of the clusters. Finally, the proposed cluster validity index is tested and validated by using five sets of artificially generated data. The results show that the proposed cluster validity index is more efficient and realistic than the former traditional indices.

This paper has been retracted as a large proportion of its contents were copied from the following paper: “A Cluster Validation Index for GK Cluster Analysis Based on Relative Degree of Sharing” by Young-Il Kim et al.

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Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Amirkabir University of Technology, (Polytechnic of Tehran) P.O. Box 15875-4413, Tehran, Iran

    Mohammad Hossein Fazel Zarandi & Elahe Neshat

  2. Department of Mechanical and Industrial Engineering, University of Toronto, 5 King College Road, Toronto, M5S2H8, Canada

    I. Burhan Türkşen

Authors
  1. Mohammad Hossein Fazel Zarandi
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  2. Elahe Neshat
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  3. I. Burhan Türkşen
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science and Engineering, York University, M3J 1P3, Toronto, Ontario, Canada

    Aijun An

  2. Institute of Computing Sciences, Poznań University of Technology, ul. Piotrowo 2, 60–965, Poznań, Poland

    Jerzy Stefanowski

  3. Department of Applied Computer Science, University of Winnipeg, R3B 2E9, Winnipeg, Manitoba, Canada

    Sheela Ramanna

  4. Department of Computer Science, University of Regina, S4S 0A2, Regina, Saskatchewan, Canada

    Cory J. Butz

  5. Department of Electrical and Computer Engineering, University of Alberta, T6G 2V4, Edmonton, Alberta, Canada

    Witold Pedrycz

  6. Institute of Compuer Science and Technology, Chongqing University of Posts and Telecommunications, 40065, Chongqing, P.R. China

    Guoyin Wang

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© 2007 Springer-Verlag Berlin Heidelberg

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Zarandi, M.H.F., Neshat, E., Türkşen, I.B. (2007). Retracted Article: A New Cluster Validity Index for Fuzzy Clustering Based on Similarity Measure. In: An, A., Stefanowski, J., Ramanna, S., Butz, C.J., Pedrycz, W., Wang, G. (eds) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. RSFDGrC 2007. Lecture Notes in Computer Science(), vol 4482. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72530-5_15

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  • DOI: https://doi.org/10.1007/978-3-540-72530-5_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72529-9

  • Online ISBN: 978-3-540-72530-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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