comparison toolboxes/FullBNT-1.0.7/netlab3.3/glmfwd.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function [y, a] = glmfwd(net, x)
+%GLMFWD	Forward propagation through generalized linear model.
+%
+%	Description
+%	Y = GLMFWD(NET, X) takes a generalized linear model data structure
+%	NET together with a matrix X of input vectors, and forward propagates
+%	the inputs through the network to generate a matrix Y of output
+%	vectors. Each row of X corresponds to one input vector and each row
+%	of Y corresponds to one output vector.
+%
+%	[Y, A] = GLMFWD(NET, X) also returns a matrix A  giving the summed
+%	inputs to each output unit, where each row corresponds to one
+%	pattern.
+%
+%	See also
+%	GLM, GLMPAK, GLMUNPAK, GLMERR, GLMGRAD
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% Check arguments for consistency
+errstring = consist(net, 'glm', x);
+if ~isempty(errstring);
+  error(errstring);
+end
+
+ndata = size(x, 1);
+
+a = x*net.w1 + ones(ndata, 1)*net.b1;
+
+switch net.outfn
+
+  case 'linear'     % Linear outputs
+    y = a;
+
+  case 'logistic'   % Logistic outputs
+    % Prevent overflow and underflow: use same bounds as glmerr
+    % Ensure that log(1-y) is computable: need exp(a) > eps
+    maxcut = -log(eps);
+    % Ensure that log(y) is computable
+    mincut = -log(1/realmin - 1);
+    a = min(a, maxcut);
+    a = max(a, mincut);
+    y = 1./(1 + exp(-a));
+
+  case 'softmax'   	% Softmax outputs
+    nout = size(a,2);
+    % Prevent overflow and underflow: use same bounds as glmerr
+    % Ensure that sum(exp(a), 2) does not overflow
+    maxcut = log(realmax) - log(nout);
+    % Ensure that exp(a) > 0
+    mincut = log(realmin);
+    a = min(a, maxcut);
+    a = max(a, mincut);
+    temp = exp(a);
+    y = temp./(sum(temp, 2)*ones(1,nout));
+    % Ensure that log(y) is computable
+    y(y<realmin) = realmin;
+
+  otherwise
+    error(['Unknown activation function ', net.outfn]);
+end