AI RESEARCH
ERICA: Quantifying Replicability of Cluster Analysis
arXiv CS.LG
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ArXi:2606.00302v1 Announce Type: cross Despite being ubiquitous in science, clustering remains a technique whose results are not quantitatively scrutinized via a framework. We present an analysis called evaluating replicability via iterative clustering assignments (ERICA) that is applied to a dataset to determine whether clusters are identified in a replicable manner. The pipeline computes a statistic that describes whether structure is found in a dataset.