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Fuzzy Hyper-Prototype Clustering

  • Conference paper
Knowledge-Based and Intelligent Information and Engineering Systems (KES 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6276))

Abstract

We propose a fuzzy hyper-prototype algorithm in this paper. This approach uses hyperplanes to represent the cluster centers in the fuzzy c-means algorithm. We present the formulation of a hyperplane-based fuzzy objective function and then derive an iterative numerical procedure for minimizing the clustering criterion. We tested the method with data degraded with random noise. The experimental results show that the proposed method is robust to clustering noisy linear structure.

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Author information

Authors and Affiliations

  1. School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, 2600, Australia

    Jin Liu & Tuan D. Pham

Authors
  1. Jin Liu
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  2. Tuan D. Pham
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Editor information

Editors and Affiliations

  1. School of Engineering, The Parade, Cardiff University, CF24 3AA, Cardiff, UK

    Rossitza Setchi

  2. Dept. of Computer Science and Software Engineering, BUckingham Building, Lion Terrace, University of Portsmouth, PO1 3HE, Portsmouth, UK

    Ivan Jordanov

  3. KES International, 145-157, St. John Street, EC1V 4PY, London, UK

    Robert J. Howlett

  4. School of Electrical and Information Engineering, University of South Australia, ,, Adelaide, Mawson Lakes Campus, 5095, SA, Australia

    Lakhmi C. Jain

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© 2010 Springer-Verlag Berlin Heidelberg

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Liu, J., Pham, T.D. (2010). Fuzzy Hyper-Prototype Clustering. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15387-7_42

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  • DOI: https://doi.org/10.1007/978-3-642-15387-7_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15386-0

  • Online ISBN: 978-3-642-15387-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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