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author | Daniel Wolff |
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date | Fri, 19 Aug 2016 13:07:06 +0200 |
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<html> <head> <title> Netlab Reference Manual gpgrad </title> </head> <body> <H1> gpgrad </H1> <h2> Purpose </h2> Evaluate error gradient for Gaussian Process. <p><h2> Synopsis </h2> <PRE> g = gpgrad(net, x, t) </PRE> <p><h2> Description </h2> <CODE>g = gpgrad(net, x, t)</CODE> takes a Gaussian Process 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 gradient <CODE>g</CODE>. Each row of <CODE>x</CODE> corresponds to one input vector and each row of <CODE>t</CODE> corresponds to one target vector. <p><h2> See Also </h2> <CODE><a href="gp.htm">gp</a></CODE>, <CODE><a href="gpcovar.htm">gpcovar</a></CODE>, <CODE><a href="gpfwd.htm">gpfwd</a></CODE>, <CODE><a href="gperr.htm">gperr</a></CODE><hr> <b>Pages:</b> <a href="index.htm">Index</a> <hr> <p>Copyright (c) Ian T Nabney (1996-9) </body> </html>