Clustering

Clustering groups observations without labels. This lecture covers k-means (iterative assignment and update), hierarchical agglomerative clustering (dendrograms and linkage rules), and how to choose the number of clusters using elbow plots and silhouette scores. We emphasise that clustering is exploratory — results depend on features, scaling, and method, and should be interpreted with caution.