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author Daniel Wolff
date Fri, 19 Aug 2016 13:07:06 +0200
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Daniel@0 1 <html>
Daniel@0 2 <head>
Daniel@0 3 <title>
Daniel@0 4 Netlab Reference Manual glmderiv
Daniel@0 5 </title>
Daniel@0 6 </head>
Daniel@0 7 <body>
Daniel@0 8 <H1> glmderiv
Daniel@0 9 </H1>
Daniel@0 10 <h2>
Daniel@0 11 Purpose
Daniel@0 12 </h2>
Daniel@0 13 Evaluate derivatives of GLM outputs with respect to weights.
Daniel@0 14
Daniel@0 15 <p><h2>
Daniel@0 16 Synopsis
Daniel@0 17 </h2>
Daniel@0 18 <PRE>
Daniel@0 19
Daniel@0 20 g = glmderiv(net, x)
Daniel@0 21 </PRE>
Daniel@0 22
Daniel@0 23
Daniel@0 24 <p><h2>
Daniel@0 25 Description
Daniel@0 26 </h2>
Daniel@0 27 <CODE>g = glmderiv(net, x)</CODE> takes a network data structure <CODE>net</CODE> and a matrix
Daniel@0 28 of input vectors <CODE>x</CODE> and returns a three-index matrix mat{g} whose
Daniel@0 29 <CODE>i</CODE>, <CODE>j</CODE>, <CODE>k</CODE>
Daniel@0 30 element contains the derivative of network output <CODE>k</CODE> with respect to
Daniel@0 31 weight or bias parameter <CODE>j</CODE> for input pattern <CODE>i</CODE>. The ordering of the
Daniel@0 32 weight and bias parameters is defined by <CODE>glmunpak</CODE>.
Daniel@0 33
Daniel@0 34 <p><h2>
Daniel@0 35 See also
Daniel@0 36 </h2>
Daniel@0 37 <PRE>
Daniel@0 38 glm, glmunpak, glmgrad</PRE>
Daniel@0 39
Daniel@0 40
Daniel@0 41 <p><hr>
Daniel@0 42 <b>Pages:</b>
Daniel@0 43 <a href="index.htm">Index</a>
Daniel@0 44 <hr>
Daniel@0 45 <p>Copyright (c) Ian T Nabney (1996-9)
Daniel@0 46
Daniel@0 47
Daniel@0 48 </body>
Daniel@0 49 </html>