Strong Consistency of K-Means Clustering

A random sample is divided into the k clusters that minimise the within cluster sum of squares. Conditions are found that ensure the almost sure convergence, as the sample size increases, of the set of means of the k clusters. The result is proved for a more general clustering criterion.