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A manifold p-spectral clustering with sparrow search algorithm

  • Data analytics and machine learning
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Abstract

Current p-spectral clustering based on Euclidean distance has good performance for partitioning data with global linear structure. However, the actual complex data or high-dimensional data often tally with the nonlinear structure. Besides, the parameter problem in p-spectral clustering has a great influence on the final clustering result. To tackle the above problems, we propose a manifold p-spectral clustering with sparrow search algorithm (SSA-MpSC). Based on the manifold learning theory, we introduce an adaptive neighborhood selection method based on expansion strategy and construct an improved manifold spatial distance to better pay attention to the local consistency of manifold data. In addition, considering the importance of parameter p to the local optimization of the algorithm, a chaotic sequence improved SSA was proposed to adjust the parameter. Increase the algorithm adaptability to datasets and the clustering accuracy by improving the similarity matrix and parameter optimization. As shown in experiment, we have also empirically verified these proprieties by testing the proposed SSA-MpSC on 3 artificial datasets as well as 6 UCI datasets with different data sizes and dimensions. The stable clustering results and higher values of NMI and ACC show that the validity and robustness of the proposed algorithm are verified.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China under Grant No. 61976216 and No. 61672522.

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Authors and Affiliations

  1. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, 221116, China

    Yanru Wang, Shifei Ding, Lijuan Wang & Shuying Du

  2. Mine Digitization Engineering Research Center of Ministry of Education of the People’s Republic of China, Xuzhou, 221116, China

    Shifei Ding

Authors
  1. Yanru Wang
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  2. Shifei Ding
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  3. Lijuan Wang
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  4. Shuying Du
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Correspondence to Shifei Ding.

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Wang, Y., Ding, S., Wang, L. et al. A manifold p-spectral clustering with sparrow search algorithm. Soft Comput 26, 1765–1777 (2022). https://doi.org/10.1007/s00500-022-06741-5

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