Mon Jul 11, 2011 5:32 am
Mon Jul 11, 2011 2:34 pm
Begin with the disjoint clustering having level L(0) = 0 and sequence number m = 0.
Find the least dissimilar pair of clusters in the current clustering, say pair (r), (s), according to
d[(r),(s)] = min d[(i),(j)]
where the minimum is over all pairs of clusters in the current clustering.
Increment the sequence number : m = m +1. Merge clusters (r) and (s) into a single cluster to form the next clustering m. Set the level of this clustering to
L(m) = d[(r),(s)]
Update the proximity matrix, D, by deleting the rows and columns corresponding to clusters (r) and (s) and adding a row and column corresponding to the newly formed cluster. The proximity between the new cluster, denoted (r,s) and old cluster (k) is defined in this way:
d[(k), (r,s)] = min d[(k),(r)], d[(k),(s)]
If all objects are in one cluster, stop. Else, go to step 2.
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