One of the biggest issue with cluster analysis is that we may happen to have to derive different conclusion when base on **different clustering methods** used  (including different linkage methods in hierarchical clustering).

I would like to know your opinion on this - **which method will you select, and how.** One might say "the best method of clustering is which gives you the right answer"; but I may question in response that cluster analysis is supposed to be an *unsupervised* technique - so how do I know which method or linkage is the right answer?

In general: is a clustering alone robust enough to rely on? Or we need a second method and get a shared result to be based on both?

My question is not only about possible ways to **validate / evaluate** clustering performance, but is broader - **on what basis do we select/prefer** one clustering method/algorithm over another one.

I know that it is very general question and very difficult to answer. I only would like to know if you have any comment or any advise or any suggestion for me to learn more about this.