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Fuzzy c-Means and Mixture Distribution Model for Clustering Based on L 1 – Space

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New Frontiers in Artificial Intelligence (JSAI 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2253))

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Abstract

This paper aims at proposing and comparing two fuzzy models and a statistical model for clustering based on L 1 -space. Clustering methods in the fuzzy models are the standard fuzzy c-means and an entropy regularization method based on L 1 -space. Furthermore, we add new variables to them for improving the cluster division. In the statistical model, a mixture distribution model based on L 1 -space is proposed and the EM algorithm is applied.

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Author information

Authors and Affiliations

  1. Graduate School of Systems and Information Engineering, University of Tsukuba, 305-8573, Ibaraki, Japan

    Takatsugu Koga

  2. Institute of Engineering Mechanics and Systems, University of Tsukuba, Tokyo

    Sadaaki Miyamoto

  3. Doctoral Program in Engineering, University of Tsukuba, Tokyo

    Osamu Takata

Authors
  1. Takatsugu Koga
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  2. Sadaaki Miyamoto
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  3. Osamu Takata
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Editor information

Editors and Affiliations

  1. Graduate School of Business Science, The University of Tsukuba, Tokyo

    Takao Terano  & Yukio Ohsawa  & 

  2. School of Engineering, The University of Tokyo, Tokyo

    Toyoaki Nishida

  3. Dept.of Computer Science, National Defense Academy, Japan

    Akira Namatame

  4. School of Medicines, Shimane Medical University, Japan

    Syusaku Tsumoto

  5. The Institute of Scientific and Industrial Research, Osaka University, Osaka

    Takashi Washio

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© 2001 Springer-Verlag Berlin Heidelberg

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Koga, T., Miyamoto, S., Takata, O. (2001). Fuzzy c-Means and Mixture Distribution Model for Clustering Based on L 1 – Space. In: Terano, T., Ohsawa, Y., Nishida, T., Namatame, A., Tsumoto, S., Washio, T. (eds) New Frontiers in Artificial Intelligence. JSAI 2001. Lecture Notes in Computer Science(), vol 2253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45548-5_33

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  • DOI: https://doi.org/10.1007/3-540-45548-5_33

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43070-4

  • Online ISBN: 978-3-540-45548-6

  • eBook Packages: Springer Book Archive

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