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Netlab Reference Manual demmdn1
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<H1> demmdn1
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<h2>
Purpose
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Demonstrate fitting a multi-valued function using a Mixture Density Network.

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Synopsis
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<PRE>
demmdn1</PRE>


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Description
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The problem consists of one input variable
<CODE>x</CODE> and one target variable <CODE>t</CODE> with data generated by
sampling <CODE>t</CODE> at equal intervals and then generating target data by
computing <CODE>t + 0.3*sin(2*pi*t)</CODE> and adding Gaussian noise. A
Mixture Density Network with 3 centres in the mixture model is trained
by minimizing a negative log likelihood error function using the scaled
conjugate gradient optimizer.

<p>The conditional means, mixing coefficients and variances are plotted
as a function of <CODE>x</CODE>, and a contour plot of the full conditional
density is also generated.

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See Also
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<CODE><a href="mdn.htm">mdn</a></CODE>, <CODE><a href="mdnerr.htm">mdnerr</a></CODE>, <CODE><a href="mdngrad.htm">mdngrad</a></CODE>, <CODE><a href="scg.htm">scg</a></CODE><hr>
<b>Pages:</b>
<a href="index.htm">Index</a>
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<p>Copyright (c) Ian T Nabney (1996-9)


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author	wolffd
date	Tue, 10 Feb 2015 15:05:51 +0000
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