In these methods the desired number of clusters is specified in advance and the ’best’ solution is chosen.

The steps in such a method are as follows:

  1. Choose initial cluster centres (essentially this is a set of observations that are far apart — each subject forms a cluster of one and its centre is the value of the variables for that subject).
  2. Assign each subject to its ’nearest’ cluster, defined in terms of the distance to the centroid.
  3. Find the centroids of the clusters that have been formed
  4. Re-calculate the distance from each subject to each centroid and move observations that are not in the cluster that they are closest to.
  5. Continue until the centroids remain relatively stable.