wolffd@0: <html> wolffd@0: <head> wolffd@0: <title> wolffd@0: Netlab Reference Manual gmmem wolffd@0: </title> wolffd@0: </head> wolffd@0: <body> wolffd@0: <H1> gmmem wolffd@0: </H1> wolffd@0: <h2> wolffd@0: Purpose wolffd@0: </h2> wolffd@0: EM algorithm for Gaussian mixture model. wolffd@0: wolffd@0: <p><h2> wolffd@0: Synopsis wolffd@0: </h2> wolffd@0: <PRE> wolffd@0: wolffd@0: [mix, options, errlog] = gmmem(mix, x, options) wolffd@0: </PRE> wolffd@0: wolffd@0: wolffd@0: <p><h2> wolffd@0: Description wolffd@0: </h2> wolffd@0: <CODE>[mix, options, errlog] = gmmem(mix, x, options)</CODE> uses the Expectation wolffd@0: Maximization algorithm of Dempster et al. to estimate the parameters of wolffd@0: a Gaussian mixture model defined by a data structure <CODE>mix</CODE>. wolffd@0: The matrix <CODE>x</CODE> represents the data whose expectation wolffd@0: is maximized, with each row corresponding to a vector. wolffd@0: wolffd@0: The optional parameters have the following interpretations. wolffd@0: wolffd@0: <p><CODE>options(1)</CODE> is set to 1 to display error values; also logs error wolffd@0: values in the return argument <CODE>errlog</CODE>. wolffd@0: If <CODE>options(1)</CODE> is set to 0, wolffd@0: then only warning messages are displayed. If <CODE>options(1)</CODE> is -1, wolffd@0: then nothing is displayed. wolffd@0: wolffd@0: <p><CODE>options(3)</CODE> is a measure of the absolute precision required of the error wolffd@0: function at the solution. If the change in log likelihood between two steps of wolffd@0: the EM algorithm is less than this value, then the function terminates. wolffd@0: wolffd@0: <p><CODE>options(5)</CODE> is set to 1 if a covariance matrix is reset to its wolffd@0: original value when any of its singular values are too small (less wolffd@0: than MIN_COVAR which has the value eps). wolffd@0: With the default value of 0 no action is taken. wolffd@0: wolffd@0: <p><CODE>options(14)</CODE> is the maximum number of iterations; default 100. wolffd@0: wolffd@0: <p>The optional return value <CODE>options</CODE> contains the final error value wolffd@0: (i.e. data log likelihood) in wolffd@0: <CODE>options(8)</CODE>. wolffd@0: wolffd@0: <p><h2> wolffd@0: Examples wolffd@0: </h2> wolffd@0: The following code fragment sets up a Gaussian mixture model, initialises wolffd@0: the parameters from the data, sets the options and trains the model. wolffd@0: <PRE> wolffd@0: wolffd@0: mix = gmm(inputdim, ncentres, 'full'); wolffd@0: wolffd@0: <p>options = foptions; wolffd@0: options(14) = 5; wolffd@0: mix = gmminit(mix, data, options); wolffd@0: wolffd@0: <p>options(1) = 1; % Prints out error values. wolffd@0: options(14) = 30; % Max. number of iterations. wolffd@0: wolffd@0: <p>mix = gmmem(mix, data, options); wolffd@0: </PRE> wolffd@0: wolffd@0: wolffd@0: <p><h2> wolffd@0: See Also wolffd@0: </h2> wolffd@0: <CODE><a href="gmm.htm">gmm</a></CODE>, <CODE><a href="gmminit.htm">gmminit</a></CODE><hr> wolffd@0: <b>Pages:</b> wolffd@0: <a href="index.htm">Index</a> wolffd@0: <hr> wolffd@0: <p>Copyright (c) Ian T Nabney (1996-9) wolffd@0: wolffd@0: wolffd@0: </body> wolffd@0: </html>