My question: what is a "standard divisive hierarchical clustering algorithm".
I have a well-defined similarity matrix, and have already carried out a clustering (with spectral + genetic clustering algorithms), but it's quite complicated.
I would like to show that a run-of-the-mill divisive hierarchical clustering algorithm gives worse results (I have means of saying which results are better).
What's important: it MUST be (for reasons too political to explain) a divisive hierarchical algorithm, and it MUST use a similarity matrix (and not, for example, a distance matrix).
I would really appreciate any advice.