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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/demmlp2.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/demmlp2.htm b/sourcecodes/bnt-master/nethelp3.3/demmlp2.htm new file mode 100644 index 00000000..ecb5e002 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/demmlp2.htm @@ -0,0 +1,41 @@ +<html> +<head> +<title> +Netlab Reference Manual demmlp2 +</title> +</head> +<body> +<H1> demmlp2 +</H1> +<h2> +Purpose +</h2> +Demonstrate simple classification using a multi-layer perceptron + +<p><h2> +Synopsis +</h2> +<PRE> +demmlp2</PRE> + + +<p><h2> +Description +</h2> +The problem consists of input data in two dimensions drawn from a mixture +of three Gaussians: two of which are assigned to a single class. An MLP +with logistic outputs trained with a quasi-Newton optimisation algorithm is +compared with the optimal Bayesian decision rule. + +<p><h2> +See Also +</h2> +<CODE><a href="mlp.htm">mlp</a></CODE>, <CODE><a href="mlpfwd.htm">mlpfwd</a></CODE>, <CODE><a href="neterr.htm">neterr</a></CODE>, <CODE><a href="quasinew.htm">quasinew</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 |