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| author | Daniel Wolff |
|---|---|
| date | Fri, 19 Aug 2016 13:07:06 +0200 |
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| children |
| rev | line source |
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| Daniel@0 | 1 <html> |
| Daniel@0 | 2 <head> |
| Daniel@0 | 3 <title> |
| Daniel@0 | 4 Netlab Reference Manual demev3 |
| Daniel@0 | 5 </title> |
| Daniel@0 | 6 </head> |
| Daniel@0 | 7 <body> |
| Daniel@0 | 8 <H1> demev3 |
| Daniel@0 | 9 </H1> |
| Daniel@0 | 10 <h2> |
| Daniel@0 | 11 Purpose |
| Daniel@0 | 12 </h2> |
| Daniel@0 | 13 Demonstrate Bayesian regression for the RBF. |
| Daniel@0 | 14 |
| Daniel@0 | 15 <p><h2> |
| Daniel@0 | 16 Synopsis |
| Daniel@0 | 17 </h2> |
| Daniel@0 | 18 <PRE> |
| Daniel@0 | 19 demev3</PRE> |
| Daniel@0 | 20 |
| Daniel@0 | 21 |
| Daniel@0 | 22 <p><h2> |
| Daniel@0 | 23 Description |
| Daniel@0 | 24 </h2> |
| Daniel@0 | 25 The problem consists an input variable <CODE>x</CODE> which sampled from a |
| Daniel@0 | 26 Gaussian distribution, and a target variable <CODE>t</CODE> generated by |
| Daniel@0 | 27 computing <CODE>sin(2*pi*x)</CODE> and adding Gaussian noise. An RBF |
| Daniel@0 | 28 network with linear outputs is trained by minimizing a sum-of-squares |
| Daniel@0 | 29 error function with isotropic Gaussian regularizer, using the scaled |
| Daniel@0 | 30 conjugate gradient optimizer. The hyperparameters <CODE>alpha</CODE> and |
| Daniel@0 | 31 <CODE>beta</CODE> are re-estimated using the function <CODE>evidence</CODE>. A graph |
| Daniel@0 | 32 is plotted of the original function, the training data, the trained |
| Daniel@0 | 33 network function, and the error bars. |
| Daniel@0 | 34 |
| Daniel@0 | 35 <p><h2> |
| Daniel@0 | 36 See Also |
| Daniel@0 | 37 </h2> |
| Daniel@0 | 38 <CODE><a href="demev1.htm">demev1</a></CODE>, <CODE><a href="evidence.htm">evidence</a></CODE>, <CODE><a href="rbf.htm">rbf</a></CODE>, <CODE><a href="scg.htm">scg</a></CODE>, <CODE><a href="netevfwd.htm">netevfwd</a></CODE><hr> |
| Daniel@0 | 39 <b>Pages:</b> |
| Daniel@0 | 40 <a href="index.htm">Index</a> |
| Daniel@0 | 41 <hr> |
| Daniel@0 | 42 <p>Copyright (c) Ian T Nabney (1996-9) |
| Daniel@0 | 43 |
| Daniel@0 | 44 |
| Daniel@0 | 45 </body> |
| Daniel@0 | 46 </html> |