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first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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wolffd@0 | 1 <html> |
wolffd@0 | 2 <head> |
wolffd@0 | 3 <title> |
wolffd@0 | 4 Netlab Reference Manual errbayes |
wolffd@0 | 5 </title> |
wolffd@0 | 6 </head> |
wolffd@0 | 7 <body> |
wolffd@0 | 8 <H1> errbayes |
wolffd@0 | 9 </H1> |
wolffd@0 | 10 <h2> |
wolffd@0 | 11 Purpose |
wolffd@0 | 12 </h2> |
wolffd@0 | 13 Evaluate Bayesian error function for network. |
wolffd@0 | 14 |
wolffd@0 | 15 <p><h2> |
wolffd@0 | 16 Synopsis |
wolffd@0 | 17 </h2> |
wolffd@0 | 18 <PRE> |
wolffd@0 | 19 e = errbayes(net, edata) |
wolffd@0 | 20 [e, edata, eprior] = errbayes(net, edata) |
wolffd@0 | 21 </PRE> |
wolffd@0 | 22 |
wolffd@0 | 23 |
wolffd@0 | 24 <p><h2> |
wolffd@0 | 25 Description |
wolffd@0 | 26 </h2> |
wolffd@0 | 27 <CODE>e = errbayes(net, edata)</CODE> takes a network data structure |
wolffd@0 | 28 <CODE>net</CODE> together |
wolffd@0 | 29 the data contribution to the error for a set of inputs and targets. |
wolffd@0 | 30 It returns the regularised error using any zero mean Gaussian priors |
wolffd@0 | 31 on the weights defined in |
wolffd@0 | 32 <CODE>net</CODE>. |
wolffd@0 | 33 |
wolffd@0 | 34 <p><CODE>[e, edata, eprior] = errbayes(net, x, t)</CODE> additionally returns the |
wolffd@0 | 35 data and prior components of the error. |
wolffd@0 | 36 |
wolffd@0 | 37 <p><h2> |
wolffd@0 | 38 See Also |
wolffd@0 | 39 </h2> |
wolffd@0 | 40 <CODE><a href="glmerr.htm">glmerr</a></CODE>, <CODE><a href="mlperr.htm">mlperr</a></CODE>, <CODE><a href="rbferr.htm">rbferr</a></CODE><hr> |
wolffd@0 | 41 <b>Pages:</b> |
wolffd@0 | 42 <a href="index.htm">Index</a> |
wolffd@0 | 43 <hr> |
wolffd@0 | 44 <p>Copyright (c) Ian T Nabney (1996-9) |
wolffd@0 | 45 |
wolffd@0 | 46 |
wolffd@0 | 47 </body> |
wolffd@0 | 48 </html> |