wolffd@0: wolffd@0:
wolffd@0:wolffd@0: post = mdnpost(mixparams, t) wolffd@0: [post, a] = mdnpost(mixparams, t) wolffd@0:wolffd@0: wolffd@0: wolffd@0:
post = mdnpost(mixparams, t)
computes the posterior
wolffd@0: probability p(j|t)
of each
wolffd@0: data vector in t
under the Gaussian mixture model represented by the
wolffd@0: corresponding entries in mixparams
. Each row of t
represents a
wolffd@0: single vector.
wolffd@0:
wolffd@0: [post, a] = mdnpost(mixparams, t)
also computes the activations
wolffd@0: a
(i.e. the probability p(t|j)
of the data conditioned on
wolffd@0: each component density) for a Gaussian mixture model.
wolffd@0:
wolffd@0:
mdngrad
, mdnprob
Copyright (c) Ian T Nabney (1996-9) wolffd@0:
David J Evans (1998) wolffd@0: wolffd@0: wolffd@0: