[mix, options, errlog] = gmmem(mix, x, options)
[mix, options, errlog] = gmmem(mix, x, options) uses the Expectation
Maximization algorithm of Dempster et al. to estimate the parameters of
a Gaussian mixture model defined by a data structure mix.
The matrix x represents the data whose expectation
is maximized, with each row corresponding to a vector.
The optional parameters have the following interpretations.
options(1) is set to 1 to display error values; also logs error
values in the return argument errlog.
If options(1) is set to 0,
then only warning messages are displayed. If options(1) is -1,
then nothing is displayed.
options(3) is a measure of the absolute precision required of the error
function at the solution. If the change in log likelihood between two steps of
the EM algorithm is less than this value, then the function terminates.
options(5) is set to 1 if a covariance matrix is reset to its
original value when any of its singular values are too small (less
than MIN_COVAR which has the value eps).
With the default value of 0 no action is taken.
options(14) is the maximum number of iterations; default 100.
The optional return value options contains the final error value
(i.e. data log likelihood) in
options(8).
mix = gmm(inputdim, ncentres, 'full');options = foptions; options(14) = 5; mix = gmminit(mix, data, options);
options(1) = 1; % Prints out error values. options(14) = 30; % Max. number of iterations.
mix = gmmem(mix, data, options);
gmm, gmminitCopyright (c) Ian T Nabney (1996-9)