[R] Compare clustering solutions to a "correct" one

[Massimo Lole]

Hello everyone,
I have a set of data, J healthy subjects, K diseased subjects, N
features for each person. I would like to clusterize my data. Since I
know that subjects are from two populations ideally I would prefer an
algorithm that first is able to discriminate them, in order to see how
it performs inside each group.
I know that R offers several clustering functions and a very
interesting clustering compare tool: cluster.stats in fpc package.
I would like to ask you if you know of any existing approach where one
cluster is considered "correct" and against it several clustering
functions (with several parameters) are run, benchmarking them and
selecting the best one.

Since I am new of R a skeleton procedure with useful functions would
help me a lot in setting up this test.

Thank you very much,
Massimo.