BNW using Octave instead of Matlab.

This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02

1 files changed, 49 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/errbayes.m b/sourcecodes/bnt-master/netlab3.3/errbayes.m
new file mode 100644
index 00000000..7c2a330b
--- /dev/null
+++ b/sourcecodes/bnt-master/netlab3.3/errbayes.m
@@ -0,0 +1,49 @@
+function [e, edata, eprior] = errbayes(net, edata)
+%ERRBAYES Evaluate Bayesian error function for network.
+%
+%	Description
+%	E = ERRBAYES(NET, EDATA) takes a network data structure  NET together
+%	the data contribution to the error for a set of inputs and targets.
+%	It returns the regularised error using any zero mean Gaussian priors
+%	on the weights defined in NET.
+%
+%	[E, EDATA, EPRIOR] = ERRBAYES(NET, X, T) additionally returns the
+%	data and prior components of the error.
+%
+%	See also
+%	GLMERR, MLPERR, RBFERR
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% Evaluate the data contribution to the error.
+if isfield(net, 'beta')
+  e1 = net.beta*edata;
+else
+  e1 = edata;
+end
+
+% Evaluate the prior contribution to the error.
+if isfield(net, 'alpha')
+   w = netpak(net);
+   if size(net.alpha) == [1 1]
+      eprior = 0.5*(w*w');
+      e2 = eprior*net.alpha;
+   else
+      if (isfield(net, 'mask'))
+         nindx_cols = size(net.index, 2);
+         nmask_rows = size(find(net.mask), 1);
+         index = reshape(net.index(logical(repmat(net.mask, ...
+            1, nindx_cols))), nmask_rows, nindx_cols);
+      else
+         index = net.index;
+      end
+      eprior = 0.5*(w.^2)*index;
+      e2 = eprior*net.alpha;
+   end
+else
+  eprior = 0;
+  e2 = 0;
+end
+
+e = e1 + e2;