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author | Daniel Wolff |
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date | Fri, 19 Aug 2016 13:07:06 +0200 |
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<html> <head> <title> Netlab Reference Manual gmmpost </title> </head> <body> <H1> gmmpost </H1> <h2> Purpose </h2> Computes the class posterior probabilities of a Gaussian mixture model. <p><h2> Synopsis </h2> <PRE> function post = gmmpost(mix, x) </PRE> <p><h2> Description </h2> This function computes the posteriors <CODE>post</CODE> (i.e. the probability of each component conditioned on the data <CODE>p(j|x)</CODE>) for a Gaussian mixture model. The data structure <CODE>mix</CODE> defines the mixture model, while the matrix <CODE>x</CODE> contains the data vectors. Each row of <CODE>x</CODE> represents a single vector. <p><h2> See Also </h2> <CODE><a href="gmm.htm">gmm</a></CODE>, <CODE><a href="gmmactiv.htm">gmmactiv</a></CODE>, <CODE><a href="gmmprob.htm">gmmprob</a></CODE><hr> <b>Pages:</b> <a href="index.htm">Index</a> <hr> <p>Copyright (c) Ian T Nabney (1996-9) </body> </html>