Nonparametric cluster significance testing with reference to a unimodal null distribution

  title={Nonparametric cluster significance testing with reference to a unimodal null distribution},
  author={Erika S Helgeson and David M. Vock and Eric Bair},
  pages={1215 - 1226}
Cluster analysis is an unsupervised learning strategy that is exceptionally useful for identifying homogeneous subgroups of observations in data sets of unknown structure. However, it is challenging to determine if the identified clusters represent truly distinct subgroups rather than noise. Existing approaches for addressing this problem tend to define clusters based on distributional assumptions, ignore the inherent correlation structure in the data, or are not suited for high‐dimension low… 
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    Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America
  • 2015
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