Like you said, such kind of test will not give me
anything that Rand index does not, except for p-value.
The null hypothesis, in my case, is that clustering
results does not match a different clustering, that
someone alse did on the same data.
And I do believe that this hypothesis is valid.
[Apology to the list for the off-topic rant...]
As it turned out, I also have a problem with LOF/GOL/etc. tests: I'd bet
most of the time when such a test is carried out, it is _not_ the only test
being done, but the p-values in the downstream analysis are almost never
adjusted for this. How
Dear Alexander,
On Wed, 24 Mar 2004, Alexander Sirotkin [at Yahoo] wrote:
Like you said, such kind of test will not give me
anything that Rand index does not, except for p-value.
The null hypothesis, in my case, is that clustering
results does not match a different clustering, that
Christian,
I think I understand your point, but I do not
completely agree with you. I also did not describe
my problem clear enough.
If you see two
clusterings on the same
data, they are identical, if they are 100%
identical, and if not, then
not.
What you are actually saying is that all
From: Alexander Sirotkin [at Yahoo] [mailto:[EMAIL PROTECTED]
Christian,
I think I understand your point, but I do not
completely agree with you. I also did not describe
my problem clear enough.
If you see two
clusterings on the same
data, they are identical, if they are 100%
On Tue, 23 Mar 2004 15:27:14 -0800 (PST), you wrote:
I was wondering, whether there is a way to have
statistical significance test for cluster agreement.
I know that I can use classAgreement() function to get
Rand index, which will give me some indication whether
the clusters agree or not, but
But what would such a test do that the rand index does not? Would you
interpret the p-value from such a test, if exists, to have the meaning that
a real test of hypothesis has? AFAIK you basically need to have the
hypotheses pinned down even before you see any data, for the inference to be
