Using the K-means clustering method as a density estimation procedure
M. Anthony Wong · DSpace@MIT (Massachusetts Institute of Technology) · 2011
A random sample of size N is divided into k clusters that minimize the within cluster sum of squares locally.This k-means clustering method can be used as a quick procedure for constructing variable-cell historgrams that have no empty cell.A histogram estimate is proposed in this paper, and is shown to be uniformly consistent in probability.1.