kmeans

[centroids,clusters,err] = kmeans(method, D, n, epochs, verbose)

 KMEANS The k-means clustering method. 

 [centroids,clusters,err] = kmeans(method, D, n, [epochs], [verbose])

   C = kmeans('batch',D,10,20);
   [C,partition] = kmeans('seq',D,D(1:10,:),20,1);

  Input and output arguments ([]'s are optional):
   method    (string) 'batch' or 'seq'
   D         (matrix) size dlen x dim, the data
             (struct) map or data struct
   n         (scalar) number of centroids
             (matrix) size n x dim, initial values for the centroids
   [epochs]  (scalar) number of training epochs, 100 by default
   [verbose] (scalar) verbose level, 0 by default

   centroids (matrix) size n x dim, the k-means centroids
   clusters  (vector) size dlen x 1, cluster number for each sample
   err       (scalar) total quantization error for the data set

 See also KMEANS_CLUSTERS.