Clustering is widely used for customer segmentation, anomaly triage, and exploratory analysis when you do not have labels. The challenge is that many clustering algorithms will always produce groups, even when the underlying structure is weak. If clusters change dramatically when you slightly perturb the data, they are hard to trust in production. Cluster stability evaluation addresses this by measuring how consistent your groupings...
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