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Comparing clusterings: an axiomatic view

ABSTRACT

This paper views clusterings as elements of a lattice. Distances between clusterings are analyzed in their relationship to the lattice. From this vantage point, we first give an axiomatic characterization of some criteria for comparing clusterings, including the variation of information and the unadjusted Rand index. Then we study other distances between partitions w.r.t these axioms and prove an impossibility result: there is no "sensible" criterion for comparing clusterings that is simultaneously (1) aligned with the lattice of partitions, (2) convexely additive, and (3) bounded.

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  1. Comparing clusterings

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    • Published in

      ACM Other conferences cover image
      ICML '05: Proceedings of the 22nd international conference on Machine learning
      August 2005
      1113 pages
      ISBN:1595931805
      DOI:10.1145/1102351

      Copyright © 2005 ACM

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 August 2005

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      Overall Acceptance Rate 448 of 1,653 submissions, 27%

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