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Math & Optimization · beginner · concept 53 of 311 · Updated Nov 4, 2026

K-Means Clustering

The simplest clustering algorithm, assigns data points to K groups by iteratively moving cluster centers to minimize within-cluster distances. Fast, intuitive, but requires choosing K upfront. It is one member of a family: hierarchical clustering builds a dendrogram of merges, DBSCAN finds arbitrary shapes by density, and Gaussian mixtures soften assignments via EM.

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Key terms

CentroidsElbow methodInertiaK selectionHierarchical clusteringDBSCANGaussian mixtures & EMSpectral clustering

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Videos

▶ StatQuest: K-means clustering ↗

StatQuest with Josh Starmer · YouTube

▶ 12. Clustering ↗

MIT OpenCourseWare · YouTube