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wolffd@0 1 <html>
wolffd@0 2 <head>
wolffd@0 3 <title>
wolffd@0 4 Netlab Reference Manual glmderiv
wolffd@0 5 </title>
wolffd@0 6 </head>
wolffd@0 7 <body>
wolffd@0 8 <H1> glmderiv
wolffd@0 9 </H1>
wolffd@0 10 <h2>
wolffd@0 11 Purpose
wolffd@0 12 </h2>
wolffd@0 13 Evaluate derivatives of GLM outputs with respect to weights.
wolffd@0 14
wolffd@0 15 <p><h2>
wolffd@0 16 Synopsis
wolffd@0 17 </h2>
wolffd@0 18 <PRE>
wolffd@0 19
wolffd@0 20 g = glmderiv(net, x)
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>g = glmderiv(net, x)</CODE> takes a network data structure <CODE>net</CODE> and a matrix
wolffd@0 28 of input vectors <CODE>x</CODE> and returns a three-index matrix mat{g} whose
wolffd@0 29 <CODE>i</CODE>, <CODE>j</CODE>, <CODE>k</CODE>
wolffd@0 30 element contains the derivative of network output <CODE>k</CODE> with respect to
wolffd@0 31 weight or bias parameter <CODE>j</CODE> for input pattern <CODE>i</CODE>. The ordering of the
wolffd@0 32 weight and bias parameters is defined by <CODE>glmunpak</CODE>.
wolffd@0 33
wolffd@0 34 <p><h2>
wolffd@0 35 See also
wolffd@0 36 </h2>
wolffd@0 37 <PRE>
wolffd@0 38 glm, glmunpak, glmgrad</PRE>
wolffd@0 39
wolffd@0 40
wolffd@0 41 <p><hr>
wolffd@0 42 <b>Pages:</b>
wolffd@0 43 <a href="index.htm">Index</a>
wolffd@0 44 <hr>
wolffd@0 45 <p>Copyright (c) Ian T Nabney (1996-9)
wolffd@0 46
wolffd@0 47
wolffd@0 48 </body>
wolffd@0 49 </html>