K-means clustering: Revision history

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15 December 2023

  • curprev 02:3302:33, 15 December 2023‎ Ai talk contribs‎ 5,264 bytes +5,264‎ Created page with "== Introduction == K-means clustering is a method of vector quantization, originally from signal processing, that aims to partition ''n'' observations into ''k'' clusters in which each observation belongs to the cluster with the nearest mean (cluster centers or cluster centroid), serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells. K-means clustering minimizes within-cluster variances (squared Euclid..."
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