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| author | ziejd2 | 2017-09-28 15:04:40 -0500 |
|---|---|---|
| committer | ziejd2 | 2017-09-28 15:04:40 -0500 |
| commit | 8070dc963753142bb86c4ed698d91fd623ed28e7 (patch) | |
| tree | d0f6dd8fc46a49b819aa55c1a90faa14d8448883 /sourcecodes/bnt-master/nethelp3.3/gmmpost.htm | |
| parent | 7cc31810d53176e805532b2789955f4eedbce6bb (diff) | |
| download | BNW-8070dc963753142bb86c4ed698d91fd623ed28e7.tar.gz | |
BNW using Octave instead of Matlab.
This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning. I am calling this BNW_1.02. It can be accessed at: compbio.uthsc.edu/BNW_1.02
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diff --git a/sourcecodes/bnt-master/nethelp3.3/gmmpost.htm b/sourcecodes/bnt-master/nethelp3.3/gmmpost.htm new file mode 100644 index 00000000..d323115f --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/gmmpost.htm @@ -0,0 +1,44 @@ +<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> \ No newline at end of file |