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Automatic clustering based on density peak detection using generalized extreme value distribution

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Abstract

Density peaks clustering (DPC) algorithm is able to get a satisfactory result with the help of artificial selecting the clustering centers, but such selection can be hard for a large amount of clustering tasks or the data set with a complex decision diagram. The purpose of this paper is to propose an automatic clustering approach without human intervention. Inspired by the visual selection rule of DPC, the judgment index which equals the lower value within density and distance (after normalization) is proposed for selecting the clustering centers. The judgment index approximately follows the generalized extreme value (GEV) distribution, and each clustering center’s judgment index is much higher. Hence, it is reasonable that the points are selected as clustering centers if their judgment indices are larger than the upper quantile of GEV. This proposed method is called density peaks clustering based on generalized extreme value distribution (DPC-GEV). Furthermore, taking the computational complexity into account, an alternative method based on density peak detection using Chebyshev inequality (DPC-CI) is also given. Experiments on both synthetic and real-world data sets show that DPC-GEV and DPC-CI can achieve the same accuracy as DPC on most data sets but consume much less time.

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Notes

  1. http://mlg.ucd.ie/datasets/3sources.html.

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Acknowledgements

The authors acknowledge the financial support from the National Natural Science Foundation of China (61473262, 61503340), Zhejiang Provincial Natural Science Foundation (LQ12A01022) and Educational Commission of Zhejiang Province (Y201121764).

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Authors and Affiliations

  1. College of Information Engineering, Zhejiang University of Technology, Hangzhou, 310023, China

    Jiajun Ding & Xiongxiong He

  2. Department of Applied Mathematics School of Science, Zhejiang University of Technology, Hangzhou, 310023, Zhejiang, China

    Junqing Yuan

  3. College of Education Science and Technology, Zhejiang University of Technology, Hangzhou, 310023, China

    Bo Jiang

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  1. Jiajun Ding
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Correspondence to Xiongxiong He.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by A. Di Nola.

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Ding, J., He, X., Yuan, J. et al. Automatic clustering based on density peak detection using generalized extreme value distribution. Soft Comput 22, 2777–2796 (2018). https://doi.org/10.1007/s00500-017-2748-7

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