Description
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. (Wikipedia, CC BY-SA)
EN note
Algorithm used to group together different objects based on similarity
Facet
Analytical
Broader terms