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1 <html>
2 <head>
3 <title>
4 Netlab Reference Manual mlperr
5 </title>
6 </head>
7 <body>
8 <H1> mlperr
9 </H1>
10 <h2>
11 Purpose
12 </h2>
13 Evaluate error function for 2-layer network.
14
15 <p><h2>
16 Synopsis
17 </h2>
18 <PRE>
19 e = mlperr(net, x, t)
20 </PRE>
21
22
23 <p><h2>
24 Description
25 </h2>
26 <CODE>e = mlperr(net, x, t)</CODE> takes a network data structure <CODE>net</CODE> together
27 with a matrix <CODE>x</CODE> of input vectors and a matrix <CODE>t</CODE> of target
28 vectors, and evaluates the error function <CODE>e</CODE>. The choice of error
29 function corresponds to the output unit activation function. Each row
30 of <CODE>x</CODE> corresponds to one input vector and each row of <CODE>t</CODE>
31 corresponds to one target vector.
32
33 <p><CODE>[e, edata, eprior] = mlperr(net, x, t)</CODE> additionally returns the
34 data and prior components of the error, assuming a zero mean Gaussian
35 prior on the weights with inverse variance parameters <CODE>alpha</CODE> and
36 <CODE>beta</CODE> taken from the network data structure <CODE>net</CODE>.
37
38 <p><h2>
39 See Also
40 </h2>
41 <CODE><a href="mlp.htm">mlp</a></CODE>, <CODE><a href="mlppak.htm">mlppak</a></CODE>, <CODE><a href="mlpunpak.htm">mlpunpak</a></CODE>, <CODE><a href="mlpfwd.htm">mlpfwd</a></CODE>, <CODE><a href="mlpbkp.htm">mlpbkp</a></CODE>, <CODE><a href="mlpgrad.htm">mlpgrad</a></CODE><hr>
42 <b>Pages:</b>
43 <a href="index.htm">Index</a>
44 <hr>
45 <p>Copyright (c) Ian T Nabney (1996-9)
46
47
48 </body>
49 </html>