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Machine Learning · Hierarchical clustering and DBSCAN
Two alternatives to k-means: agglomerative clustering, which builds a tree of merges, and DBSCAN, which finds dense regions of any shape and labels noise.
- DBSCAN needs no k: it grows clusters from dense regions and marks isolated points as noise.
- k-means assumes round, similar-sized clusters; DBSCAN does not.