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Hierarchy as a Clustering Structure

  • Boris Mirkin
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 11)

Abstract

  • Directions for representing and comparing hierarchies are discussed.

  • Clustering methods that are invariant under monotone dissimilarity transformations are analyzed.

  • Most recent theories and methods concerning such concepts as ultrametric, tree metric, Robinson matrix, pyramid, and weak hierarchy are presented.

  • A linear theory for binary hierarchy is proposed to allow decomposing the data entries, as well as covariances, by the clusters.

Keywords

Span Tree Minimum Span Tree Cluster Structure Dissimilarity Measure Node Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Boris Mirkin
    • 1
  1. 1.DIMACSRutgers UniversityUSA

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