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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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<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>