Math & Optimization · beginner · concept 37 of 176

📐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.