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| author | ziejd2 | 2017-09-28 15:04:40 -0500 |
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| committer | ziejd2 | 2017-09-28 15:04:40 -0500 |
| commit | 8070dc963753142bb86c4ed698d91fd623ed28e7 (patch) | |
| tree | d0f6dd8fc46a49b819aa55c1a90faa14d8448883 /sourcecodes/bnt-master/nethelp3.3/demprior.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/demprior.htm b/sourcecodes/bnt-master/nethelp3.3/demprior.htm new file mode 100644 index 00000000..02f5a000 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/demprior.htm @@ -0,0 +1,44 @@ +<html> +<head> +<title> +Netlab Reference Manual demprior +</title> +</head> +<body> +<H1> demprior +</H1> +<h2> +Purpose +</h2> +Demonstrate sampling from a multi-parameter Gaussian prior. + +<p><h2> +Synopsis +</h2> +<PRE> +demprior</PRE> + + +<p><h2> +Description +</h2> +This function plots the functions represented by a multi-layer perceptron +network when the weights are set to values drawn from a Gaussian prior +distribution. The parameters <CODE>aw1</CODE>, <CODE>ab1</CODE> <CODE>aw2</CODE> and <CODE>ab2</CODE> +control the inverse variances of the first-layer weights, the hidden unit +biases, the second-layer weights and the output unit biases respectively. +Their values can be adjusted on a logarithmic scale using the sliders, or +by typing values into the text boxes and pressing the return key. + +<p><h2> +See Also +</h2> +<CODE><a href="mlp.htm">mlp</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 |