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A Bio Inspired Fuzzy K-Modes Clustring Algorithm

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Neural Information Processing (ICONIP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7665))

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Abstract

This paper proposes a bio inspired fuzzy K-Modes clustering algorithm using fuzzy particle swarm optimization (FPSO) and fuzzy k-modes (FK-Modes) algorithm for clustering categorical data. It integrates concepts of FK-Modes algorithm to handle the uncertainty phenomena and FPSO to reach global optimal solution of clustering optimization problem. The proposed FPSO-FK-Modes algorithm was implemented and evaluated using slandered benchmark data sets and performance measures. Experimental results showed that the proposed FPSO-FK-Modes algorithm performed well compared with FK-modes and Genetic FK-modes (GA- FK-modes) algorithm using adjusted rand index.

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Author information

Authors and Affiliations

  1. Faculty of Computers and Information, Cairo University, Egypt

    Omar S. Soliman, Doaa A. Saleh & Samaa Rashwan

Authors
  1. Omar S. Soliman
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  2. Doaa A. Saleh
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  3. Samaa Rashwan
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Editor information

Editors and Affiliations

  1. Texas A&M University at Qatar, Education City, P.O. Box 23874, Doha, Qatar

    Tingwen Huang

  2. Department of Control Science and Engineering, Huazhong University of Science and Technology, 1037 Luoyu Road, 430074, Wuhan, Hubei, China

    Zhigang Zeng

  3. College of Computer Science, Chongqing University, 174 Shazhengjie Street, 400044, Chongqing, China

    Chuandong Li

  4. Department of Electronic Engineering, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Chi Sing Leung

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© 2012 Springer-Verlag Berlin Heidelberg

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Soliman, O.S., Saleh, D.A., Rashwan, S. (2012). A Bio Inspired Fuzzy K-Modes Clustring Algorithm. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7665. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34487-9_80

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  • DOI: https://doi.org/10.1007/978-3-642-34487-9_80

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34486-2

  • Online ISBN: 978-3-642-34487-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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