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DPC-LG: Density peaks clustering based on logistic distribution and gravitation

Author

Listed:
  • Jiang, Jianhua
  • Chen, Yujun
  • Hao, Dehao
  • Li, Keqin

Abstract

The Density Peaks Clustering (DPC) algorithm, published in Science, is a novel density-based clustering approach. Gravitation-based Density Peaks Clustering (GDPC) algorithm, inherited the advantages of DPC, is an improved algorithm. GDPC is able to detect outliers and to find the number of clusters correctly. However, it still has some problems in: (1) processing some data sets of varying densities; (2) processing some data sets of irregular shapes. An improved density clustering algorithm, named as DPC-LG, is proposed to overcome some weakness of GDPC. It can be seen from experimental results that the DPC-LG algorithm is more feasible and effective, compared with AP, DPC and GDPC.

Suggested Citation

  • Jiang, Jianhua & Chen, Yujun & Hao, Dehao & Li, Keqin, 2019. "DPC-LG: Density peaks clustering based on logistic distribution and gravitation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 25-35.
    • Handle: RePEc:eee:phsmap:v:514:y:2019:i:c:p:25-35
    DOI: 10.1016/j.physa.2018.09.002
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    References listed on IDEAS

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    1. Jiang, Jianhua & Hao, Dehao & Chen, Yujun & Parmar, Milan & Li, Keqin, 2018. "GDPC: Gravitation-based Density Peaks Clustering algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 345-355.
    2. Dong, Gaogao & Tian, Lixin & Du, Ruijin & Fu, Min & Stanley, H. Eugene, 2014. "Analysis of percolation behaviors of clustered networks with partial support–dependence relations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 394(C), pages 370-378.
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    Cited by:

    1. Jiang, Jianhua & Chen, Yujun & Meng, Xianqiu & Wang, Limin & Li, Keqin, 2019. "A novel density peaks clustering algorithm based on k nearest neighbors for improving assignment process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 702-713.
    2. Yu, Hui & Chen, LuYuan & Yao, JingTao & Wang, XingNan, 2019. "A three-way clustering method based on an improved DBSCAN algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).

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