kmeans uses the k-means++ algorithm for centroid initialization and squared Euclidean distance by default. It is good practice to search for lower, local minima by setting the 'Replicates' name-value pair argument. idx is a vector of predicted cluster indices corrresponding to the observations in X. C is a 3-by-2 matrix containing the final centroid locations. Use kmeans to compute the distance from each centroid to points on a grid. To do this, pass the centroids (C) and points on a grid to kmeans, and implement one iteration of the algorithm.

Filename	Size	Update
statistics_kmeans.m	9658	2017-06-26

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