As a way out in such cases, one could try to reduce the set of variables
to a much smaller set by means of some dimension reduction technique.
This idea gives rise to the problem of looking simultaneously for a clustering
and a variable reduction that capture in an (jointly) optimal way the
structure behind the data at hand.