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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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<html> <head> <title> Netlab Reference Manual mlperr </title> </head> <body> <H1> mlperr </H1> <h2> Purpose </h2> Evaluate error function for 2-layer network. <p><h2> Synopsis </h2> <PRE> e = mlperr(net, x, t) </PRE> <p><h2> Description </h2> <CODE>e = mlperr(net, x, t)</CODE> takes a network data structure <CODE>net</CODE> together with a matrix <CODE>x</CODE> of input vectors and a matrix <CODE>t</CODE> of target vectors, and evaluates the error function <CODE>e</CODE>. The choice of error function corresponds to the output unit activation function. Each row of <CODE>x</CODE> corresponds to one input vector and each row of <CODE>t</CODE> corresponds to one target vector. <p><CODE>[e, edata, eprior] = mlperr(net, x, t)</CODE> additionally returns the data and prior components of the error, assuming a zero mean Gaussian prior on the weights with inverse variance parameters <CODE>alpha</CODE> and <CODE>beta</CODE> taken from the network data structure <CODE>net</CODE>. <p><h2> See Also </h2> <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> <b>Pages:</b> <a href="index.htm">Index</a> <hr> <p>Copyright (c) Ian T Nabney (1996-9) </body> </html>