--- title: R: K-Means --- [R 3.0 icon]What does K-MEANS do ? Program K-MEANS computes a non-hierarchical clustering by minimization of the within-group variance, following several variants of the method originally proposed by MacQueen (1967), to which he gave the name k-means. This is a partitioning method for a group of objects, and not a method of hierarchical classification. The user decides how many groups, k, she wants to obtain from the program. The k-means algorithm followed here is the one described on page 163 of Anderberg (1973). The present program computes the clustering with or without contiguity constraint (spatial or temporal), following the user's request. It complements the hierarchical clustering programs of the R package, which implement various algorithms of clustering without constraint ( CLUSTER in the Macintosh version) or with contiguity constraint ( BIOGEO and CHRONO).
Last updated on Saturday, March 30, 2013 by Philippe Casgrain