HDBSCAN ported to Observable notebooks with clustering examples for 30DayMapChallenge
leland_mcinnes · x · 2026-11-08
For #30DayMapChallenge day 4 ("Clusters"), Fil ported HDBSCAN to an Observable notebook with worked examples — shared by HDBSCAN author Leland McInnes.
The accompanying visuals show the algorithm in action: UK geographic points colored into city clusters (London, Birmingham, Manchester, etc.), MNIST digits forming natural 0-9 clusters in embedding space, and a penguins dataset demo using a minimum spanning tree on mutual reachability distance to explain cluster structure. A runnable learning resource for anyone wanting to understand HDBSCAN or cluster geographic/embedding data.
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