A density-based method for selection of the initial clustering centers of K-means algorithm

@article{Du2017ADM,
  title={A density-based method for selection of the initial clustering centers of K-means algorithm},
  author={Xin Du and N. Xu and Cailan Zhou and Shihui Xiao},
  journal={2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)},
  year={2017},
  pages={2509-2512}
}
  • Xin Du, N. Xu, +1 author Shihui Xiao
  • Published 2017
  • Mathematics
  • 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)
The initial clustering centers of traditional K-means algorithm are randomly generated from a data set, clustering effect is not very stable. Aimed at this problem, this paper puts forward a kind of optimal selection of the initial clustering center of K-means algorithm based on density, by calculating the local density of each data point and the minimum distance between that point and any other point with higher local density, choose K points with higher local density as the initial clustering… Expand
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