Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 457-460.

• Big Data & Data Mining • Previous Articles     Next Articles

Density Peak Clustering Algorithm Based on Grid Data Center

LI Xiao-guang, SHAO Chao   

  1. School of Computer & Information Engineering,Henan University of Economics and Law,Zhengzhou 450046,China
  • Online:2019-06-14 Published:2019-07-02

Abstract: A density peak clustering algorithm based on the grid data center was proposed.The computational complexity of the clustering process is reduced by meshing the dataset.Firstly,the dataset space is divided into grids with the same size,the density value of each grid is composed of the number of data objects that are contained in the grid and the decayed number of the data objects in its adjacent grids,and the distance value of each grid is defined as the nearest distance from its data center to the data center of another grid which has a higher density.Then,the cluster center grids are found since these grids always have high density value and large distance value.Finally,a density-based division approach is used to complete the duty of clustering.The simulation experiments performed on UCI artificial data set show that this algorithm can effectively cluster large-scale data with high clustering accuracy in a short period of time.

Key words: Clustering, Data center, Decision graph, Density peak, Grid

CLC Number: 

  • TP181
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