diff toolboxes/FullBNT-1.0.7/netlab3.3/glminit.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/netlab3.3/glminit.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,36 @@
+function net = glminit(net, prior)
+%GLMINIT Initialise the weights in a generalized linear model.
+%
+%	Description
+%
+%	NET = GLMINIT(NET, PRIOR) takes a generalized linear model NET and
+%	sets the weights and biases by sampling from a Gaussian distribution.
+%	If PRIOR is a scalar, then all of the parameters (weights and biases)
+%	are sampled from a single isotropic Gaussian with inverse variance
+%	equal to PRIOR. If PRIOR is a data structure similar to that in
+%	MLPPRIOR but for a single layer of weights, then the parameters are
+%	sampled from multiple Gaussians according to their groupings (defined
+%	by the INDEX field) with corresponding variances (defined by the
+%	ALPHA field).
+%
+%	See also
+%	GLM, GLMPAK, GLMUNPAK, MLPINIT, MLPPRIOR
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+errstring = consist(net, 'glm');
+if ~isempty(errstring);
+  error(errstring);
+end
+if isstruct(prior)
+  sig = 1./sqrt(prior.index*prior.alpha);
+  w = sig'.*randn(1, net.nwts); 
+elseif size(prior) == [1 1]
+  w = randn(1, net.nwts).*sqrt(1/prior);
+else
+  error('prior must be a scalar or a structure');
+end  
+
+net = glmunpak(net, w);
+