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The upper bound of the optimal number of clusters in fuzzy clustering

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Abstract

The upper bound of the optimal number of clusters in clustering algorithm is studied in this paper. A new method is proposed to solve this issue. This method shows that the rulec max ≤ √n, which is popular in current papers, is reasonable in some sense. The above conclusion is tested and analyzed by some typical examples in the literature, which demonstrates the validity of the new method.

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Authors and Affiliations

  1. Department of Information Science, School of Mathematical Science, Peking University, 100871, Beijing, China

    Yu Jian & Cheng Qiansheng

  2. Department of Computer Science and Technology, North Jiaotang University, 100044, Beijing, China

    Yu Jian

Authors
  1. Yu Jian
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  2. Cheng Qiansheng
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Correspondence to Yu Jian.

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Yu, J., Cheng, Q. The upper bound of the optimal number of clusters in fuzzy clustering. Sci China Ser F 44, 119–125 (2001). https://doi.org/10.1007/BF02713970

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  • DOI: https://doi.org/10.1007/BF02713970

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