Glossary · Phase 3 · Machine learning
Dendrogram
The tree of merges hierarchical clustering builds; cutting it at a height gives a set of clusters.
Try it now
Two crescents and a few stray points. The ring shows the radius around one point. Slide the radius from small to large.
Learn it properly
Clusters of any shape: DBSCAN and hierarchies · Why k-means needs round clusters, DBSCAN's core points and noise, and hierarchical clustering with its linkages. About 30 minutes.
Other terms from the same lesson
- adjusted Rand index: A score for how closely two groupings of the same points agree: 1 means identical, 0 means no better than chance.
- DBSCAN: Density-based clustering: clusters grow through crowded points within a radius, and points no cluster reaches are labeled noise.
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