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A novel cluster validity index for fuzzy C-means algorithm

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Abstract

To overcome the main problem of the cluster number in many clustering applications, a new clustering approach with improved morphology similarity distance and the novel cluster validity index is proposed in this paper. An optimized morphology similarity distance based on the Standard Euclidean distance and ReliefF algorithm is used to create a new validity index, which can balance the intra-cluster consistency and inter-cluster consistency. The proposed validity index is combined with fuzzy C-means to produce a creative algorithm simply named the OMS-OSC algorithm. Experimental results obtained using different artificial data sets and real-world data sets show that the new algorithm can not only yield good performance but also detect the correct cluster number.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China with the Grant Nos. 61573157, 61561024 and 61562038, the Fund of Natural Science Foundation of Guangdong Province of China with the Grant No. 2014A030313454, the Key Project of Natural Statistical Science and Research with the Grant No. 2015LZ30.

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Authors and Affiliations

  1. College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China

    Shuling Yang, Kangshun Li & Wei Li

  2. Shenzhen Saudi Statistician Company Limited, Shenzhen, China

    Kangshun Li

  3. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong Province, China

    Zhengping Liang

  4. School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, China

    Wei Li

  5. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China

    Yu Xue

Authors
  1. Shuling Yang
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  2. Kangshun Li
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  3. Zhengping Liang
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  4. Wei Li
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  5. Yu Xue
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Correspondence to Kangshun Li.

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

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Communicated by V. Loia.

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Yang, S., Li, K., Liang, Z. et al. A novel cluster validity index for fuzzy C-means algorithm. Soft Comput 22, 1921–1931 (2018). https://doi.org/10.1007/s00500-016-2453-y

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