How do you evaluate clustering quality when ground truth labels are unavailable?

You use internal metrics like Silhouette Score, Davies-Bouldin Index, and inertia-based heuristics.

Since clustering is unsupervised, evaluation relies on geometric properties: cohesion within clusters and separation between clusters. Silhouette score combines both, while Davies-Bouldin measures cluster similarity ratios.