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Most Influential ICML 2005 Paper · 2026-03 edition

Comparing Clusterings: An Axiomatic View

Marina Meilǎ

Venue
International Conference on Machine Learning (ICML) 2005
Recognition
Most Influential ICML 2005 Paper (Rank No. 6)
Edition
2026-03
Impact factor
7
Certificate ID
e1be9ef14420712b

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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