How to evaluate clustering with ground truth?

• URL: http://arxiv.org/abs/2606.27061v1
• Date: Thu, 25 Jun 2026 14:07:17 GMT
• Title: How to evaluate clustering with ground truth?
• Abstract summary: We review the most common external validity indexes focusing on set-matching-based measures.<n>We recommend centroid index (CI), because it is an intuitive cluster-level measure with an explainable result.
• Score: 2.335152769484957
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: External indexes can be used for cluster evaluation when ground truth is available. We review the most common external validity indexes focusing on set-matching-based measures. We recommend centroid index (CI), because it is an intuitive cluster-level measure with an explainable result. If we need a more fine-tuned, point-level measure, there are more choices. Pair-set index (PSI) provides a normalized score which is not biased by cluster sizes. If all points should matter equally, then clustering accuracy (ACC) or any other set-matching measure is suitable.

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