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

first hg version after svn

+function [h, hdata] = hbayes(net, hdata) 
+%HBAYES	Evaluate Hessian of Bayesian error function for network.
+%
+%	Description
+%	H = HBAYES(NET, HDATA) takes a network data structure NET together
+%	the data contribution to the Hessian for a set of inputs and targets.
+%	It returns the regularised Hessian using any zero mean Gaussian
+%	priors on the weights defined in NET.  In addition, if a MASK is
+%	defined in NET, then the entries in H that correspond to weights with
+%	a 0 in the mask are removed.
+%
+%	[H, HDATA] = HBAYES(NET, HDATA) additionally returns the data
+%	component of the Hessian.
+%
+%	See also
+%	GBAYES, GLMHESS, MLPHESS, RBFHESS
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+if (isfield(net, 'mask'))
+  % Extract relevant entries in Hessian
+  nmask_rows = size(find(net.mask), 1);
+  hdata = reshape(hdata(logical(net.mask*(net.mask'))), ...
+     nmask_rows, nmask_rows);
+  nwts = nmask_rows;
+else
+  nwts = net.nwts;
+end
+if isfield(net, 'beta')
+  h = net.beta*hdata;
+else
+  h = hdata;
+end
+
+if isfield(net, 'alpha')
+  if size(net.alpha) == [1 1]
+    h = h + net.alpha*eye(nwts);
+  else
+    if isfield(net, 'mask')
+      nindx_cols = size(net.index, 2);
+      index = reshape(net.index(logical(repmat(net.mask, ...
+         1, nindx_cols))), nmask_rows, nindx_cols);
+    else
+      index = net.index;
+    end
+    h = h + diag(index*net.alpha);
+  end 
+end