Given distance metric and N vectors, what would be algorithm or procedure to decide how many clusters to form ? My question is not how to cluster, but how to decide how many clusters is the most optimal number to use to represent the N vectors i.e. most economically.
To say it another way use the least number of clusters to represent the most of the N-vectors.
hmmm... if I have dendogram-graph would comparison of "nodes" distance at the same level qualify as a good way to approach the problem. thinking loudly : start from the root going down the levels until the average distance between 'cluster-nodes' reach some value ? How would I calculate that limit-value ? entropy?