Stability of clusters in a unsupervised machine learning
From scikit-learn document Link-

Given the knowledge of the ground truth class assignments labels_true and our clustering algorithm assignments of the same samples labels_pred, the (adjusted or unadjusted) Rand index is a function that measures the similarity of the two assignments

labels_true = [0, 0, 0, 1, 1, 1]
labels_pred = [0, 0, 1, 1, 2, 2]
metrics.rand_score(labels_true, labels_pred)

2.3.10.1.2. Drawbacks

Contrary to inertia, the (adjusted or unadjusted) Rand index requires knowledge of the ground truth classes which is almost never available in practice or requires manual assignment by human annotators (as in the supervised learning setting).