R help - Jan 2004 - predict.lda problem with posterior probabilities

With predict.lda the posterior probabilities only relate to the existing
Class definitions.  This is fine for Class definitions like gender but it is
a problem when new data does not necessarily belong to an existing Class.
Is there a classification method that gives posterior probabilities for
Class membership and does not assume the new data must belong to one of the
existing Classes?  A new class would then be indicated by low posterior
probabilities for all the existing Classes.

Thanks
Mike White

At 04:23 AM 1/23/2004, Mike White wrote:
 >With predict.lda the posterior probabilities only relate to the existing
 >Class definitions.  This is fine for Class definitions like gender but it
is
 >a problem when new data does not necessarily belong to an existing Class.
 >Is there a classification method that gives posterior probabilities for
 >Class membership and does not assume the new data must belong to one of the
 >existing Classes?  A new class would then be indicated by low posterior
 >probabilities for all the existing Classes.


For discriminant analysis, one of of doing this would be to use "typicality
probabilities", sometimes called "inverse probabilities".  This
is
discussed in Huberty's Applied Discriminant Analysis, Wiley 1994 (and other 
sources), and is used relatively commonly in the paleoanthropological 
literature where researchers try to "classify" a fossil into a matrix
of
modern forms to which it is already known that the fossil does not 
belong.  The question is whether the fossil has a modern analog or whether 
it really is dissimilar from any modern form.