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Accelerated Matrix Factorisation Method for Fuzzy Clustering

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Neural Information Processing (ICONIP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10638))

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Abstract

Factorised fuzzy c-means (F-FCM) based on semi nonnegative matrix factorization is a new approach for fuzzy clustering. It does not need the weighting exponent parameter compared with traditional fuzzy c-means, and not sensitive to initial conditions. However, F-FCM does not propose an efficient method to solve the constrained problem, and just suggests to use a lsqlin() function in MATLAB which lead to slow convergence rate and nonconvergence. In this paper, we propose a method to accelerate the convergence rate of F-FCM combining with a non-monotone accelerate proximal gradient (nmAPG) method. We also propose an efficient method to solve the proximal mapping problem when implementing nmAPG. Finally, the experiment results on synthetic and real-world datasets show the performances and feasibility of our method.

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Acknowledgement

This research was supported by the National Natural Science Foundation of China (Grant Nos. 11627802, 51678249), by the Science and Technology Projects of Guangdong (2013A011403003), and by the Science and Technology Projects of Guangzhou (201508010023).

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Authors and Affiliations

  1. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510640, China

    Mingjun Zhan & Bo Li

Authors
  1. Mingjun Zhan
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  2. Bo Li
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Corresponding author

Correspondence to Bo Li .

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Editors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Derong Liu

  2. Guangdong University of Technology, Guangzhou, China

    Shengli Xie

  3. South China University of Technology, Guangzhou, China

    Yuanqing Li

  4. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Dongbin Zhao

  5. King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia

    El-Sayed M. El-Alfy

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Zhan, M., Li, B. (2017). Accelerated Matrix Factorisation Method for Fuzzy Clustering. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10638. Springer, Cham. https://doi.org/10.1007/978-3-319-70139-4_12

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  • DOI: https://doi.org/10.1007/978-3-319-70139-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70138-7

  • Online ISBN: 978-3-319-70139-4

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