Mercurial > hg > camir-aes2014
diff toolboxes/FullBNT-1.0.7/netlab3.3/glmgrad.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/toolboxes/FullBNT-1.0.7/netlab3.3/glmgrad.m Tue Feb 10 15:05:51 2015 +0000 @@ -0,0 +1,36 @@ +function [g, gdata, gprior] = glmgrad(net, x, t) +%GLMGRAD Evaluate gradient of error function for generalized linear model. +% +% Description +% G = GLMGRAD(NET, X, T) takes a generalized linear model data +% structure NET together with a matrix X of input vectors and a matrix +% T of target vectors, and evaluates the gradient G of the error +% function with respect to the network weights. The error function +% corresponds to the choice of output unit activation function. Each +% row of X corresponds to one input vector and each row of T +% corresponds to one target vector. +% +% [G, GDATA, GPRIOR] = GLMGRAD(NET, X, T) also returns separately the +% data and prior contributions to the gradient. +% +% See also +% GLM, GLMPAK, GLMUNPAK, GLMFWD, GLMERR, GLMTRAIN +% + +% Copyright (c) Ian T Nabney (1996-2001) + +% Check arguments for consistency +errstring = consist(net, 'glm', x, t); +if ~isempty(errstring); + error(errstring); +end + +y = glmfwd(net, x); +delout = y - t; + +gw1 = x'*delout; +gb1 = sum(delout, 1); + +gdata = [gw1(:)', gb1]; + +[g, gdata, gprior] = gbayes(net, gdata);