I'm a newbie in cluster analysis so please excuse me if my question seems to be very basic. I'm using SPSS and Matlab for performing cluster analysis in a variety of datasets. Dendograms are great for visualising the results. However, they are not helpful for comparing the results produced by different clustering methods or algorithms. Is there a standard way to do this? Does anybody had use a Database for this purpose? I'm kind of proficient in Access-VBA, but I'm lost in what data I should store (resemblance matrix, cophenetic matrix, etc) and how to transform them in a comprehensive database matrix.
Wikipedia has a section dedicated to comparing ("evaluating") clustering results:
However, these methods will essentially give you some number.
Cluster analysis is an explorative method, as such you'll have to investigate the discovered structure manually, whether it is more sensible than the structure you knew before, or not. One might say that there is no "good" or "bad" in cluster analysis, only "new" or "already known". But there is "new and useful" and "new but uninteresting" IMHO.
There is some work in the "multi view" clustering community on how to compare clusterings. If you want to generate a diverse clustering, you have to measure similarity.
See e.g. MultiClust 2011: http://dme.rwth-aachen.de/en/MultiClust2011#prog
I made a mistake by calling the "measure" I want to get steps. I meant heights. It seems that Matlab can provide me what I'm looking for, by using the inconsistent function:
Now using the right "term" my google search returns results. It seems I don't have to put too much effort in getting the precise values of the heights according to the next quote:
Few investigators place much reliance on the precise values of the heights in a dendrogram, partly because of the difficulties referred (...); and patly because there is sometimes interest in comparing dendrograms obtained by analyzing the same data set by more than one method of analysis, when the heights in the different dendrograms may not be commesurate.
Thank you very much Anony-Mousse for your help
All the best,