Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection

@article{Campello2015HierarchicalDE,
  title={Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection},
  author={R. Campello and Davoud Moulavi and A. Zimek and J. Sander},
  journal={ACM Trans. Knowl. Discov. Data},
  year={2015},
  volume={10},
  pages={5:1-5:51}
}
  • R. Campello, Davoud Moulavi, +1 author J. Sander
  • Published 2015
  • Computer Science
  • ACM Trans. Knowl. Discov. Data
  • An integrated framework for density-based cluster analysis, outlier detection, and data visualization is introduced in this article. The main module consists of an algorithm to compute hierarchical estimates of the level sets of a density, following Hartigan’s classic model of density-contour clusters and trees. Such an algorithm generalizes and improves existing density-based clustering techniques with respect to different aspects. It provides as a result a complete clustering hierarchy… CONTINUE READING
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