DM: Clustering algorithm for high-dimensional Boolean space

[Rao, Bharat]

Hello,

I'm looking to cluster a dataset where the
a) data has high-dimensionality (50<n<1000)
b) relatively few samples ( M=O(n), and occasionally M < n)
c) and is completely Boolean (all variables are 0/1).

        [Obviously clustering will be hard, and quite possibly
         I will end up with a bunch of singleton clusters.  But
         I'd like to try running some existing algorithms on this
         data, at least for benchmarking purposes, before trying
         to develop new algorithms.]

Can anyone point me to some existing implemented algorithms that
cluster Boolean data.  (I have already requested a copy of COBWEB
from Doug Fisher, and realize that AutoClass is not suited for Boolean
data.)

Also, any pointers to work on constructive induction that may be
relevant
for constructing new features to help clustering would be appreciated.

Thanks for any help,

Bharat

        [Obviously clustering will be hard, and most likely
         I will end up with a bunch of singleton clusters.  But
         I'd like to try running some existing algorithms on this
         data, at least for benchmarking purposes, before trying
         to develop new algorithms.]

R. Bharat Rao,          E-mail:bharat@scr.siemens.com [PGP WELCOME] 
Adaptive Information & Signal Processing, Siemens Corporate Research
US Mail: 755 College Road East, Princeton, NJ 08540
Phones: (609)734-6531(O) (609)734-6565(F)
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