 Usage:  ckm = kmeans (x, b, it, {w, {m}})   

 

 Input:



  x                      n x p matrix data matrix 

                         

                         

  b                      n x 1 matrix: Initial partition (for example random generated 

                         

                         numbers of clusters 1,2,...,K 

                         

                         

  it                     maximal number of iterations 

                         

                         

  w                      p x 1 matrix with the weights of column points 

                         

                         

  m                      n x 1 matrix of weights (masses) of row points 

                         

                         

 Output:



  cm.g                   n x 1 matrix containing the final partition which gives a 

                         

                         minimum sum of within cluster variances 

                         

                         

  cm.c                   k x p matrix of means (centroids) of the K clusters 

                         

                         

  cm.v                   k x p matrix of within cluster variances divided by the weight 

                         

                         (mass) of clusters 

                         

                         

  cm.s                   k x 1 matrix of the weight (mass) of clusters 

                         

                         

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(C) MD*TECH Method and Data Technologies, 21.9.2000

