Beyond Hartigan Consistency: Merge Distortion Metric for Hierarchical Clustering

  title={Beyond Hartigan Consistency: Merge Distortion Metric for Hierarchical Clustering},
  author={Justin Eldridge and Mikhail Belkin and Yusu Wang},
Hierarchical clustering is a popular method for analyzing data which associates a tree to a dataset. Hartigan consistency has been used extensively as a framework to analyze such clustering algorithms from a statistical point of view. Still, as we show in the paper, a tree which is Hartigan consistent with a given density can look very different than the correct limit tree. Specifically, Hartigan consistency permits two types of undesirable configurations which we term over-segmentation and… CONTINUE READING
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