arXiv Machine Learning June 4, 2026 By Alexander J. Gates

Unifying Information-Theoretic and Pair-Counting Clustering Similarity

Read the original on arXiv Machine Learning →

arXiv:2511. 03000v2 Announce Type: replace-cross Abstract: Comparing clusterings is central to evaluating unsupervised models, yet the many existing similarity measures can produce widely divergent, sometimes contradictory, evaluations.

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