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author wolffd
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wolffd@0 1 <html>
wolffd@0 2 <head>
wolffd@0 3 <title>
wolffd@0 4 Netlab Reference Manual gpgrad
wolffd@0 5 </title>
wolffd@0 6 </head>
wolffd@0 7 <body>
wolffd@0 8 <H1> gpgrad
wolffd@0 9 </H1>
wolffd@0 10 <h2>
wolffd@0 11 Purpose
wolffd@0 12 </h2>
wolffd@0 13 Evaluate error gradient for Gaussian Process.
wolffd@0 14
wolffd@0 15 <p><h2>
wolffd@0 16 Synopsis
wolffd@0 17 </h2>
wolffd@0 18 <PRE>
wolffd@0 19 g = gpgrad(net, x, t)
wolffd@0 20 </PRE>
wolffd@0 21
wolffd@0 22
wolffd@0 23 <p><h2>
wolffd@0 24 Description
wolffd@0 25 </h2>
wolffd@0 26 <CODE>g = gpgrad(net, x, t)</CODE> takes a Gaussian Process data structure <CODE>net</CODE> together
wolffd@0 27 with a matrix <CODE>x</CODE> of input vectors and a matrix <CODE>t</CODE> of target
wolffd@0 28 vectors, and evaluates the error gradient <CODE>g</CODE>. Each row
wolffd@0 29 of <CODE>x</CODE> corresponds to one input vector and each row of <CODE>t</CODE>
wolffd@0 30 corresponds to one target vector.
wolffd@0 31
wolffd@0 32 <p><h2>
wolffd@0 33 See Also
wolffd@0 34 </h2>
wolffd@0 35 <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>
wolffd@0 36 <b>Pages:</b>
wolffd@0 37 <a href="index.htm">Index</a>
wolffd@0 38 <hr>
wolffd@0 39 <p>Copyright (c) Ian T Nabney (1996-9)
wolffd@0 40
wolffd@0 41
wolffd@0 42 </body>
wolffd@0 43 </html>