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, 60 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/hesschek.m b/sourcecodes/bnt-master/netlab3.3/hesschek.m
new file mode 100644
index 00000000..ffd7253d
--- /dev/null
+++ b/sourcecodes/bnt-master/netlab3.3/hesschek.m
@@ -0,0 +1,60 @@
+function h = hesschek(net, x, t)
+%HESSCHEK Use central differences to confirm correct evaluation of Hessian matrix.
+%
+%	Description
+%
+%	HESSCHEK(NET, X, T) takes a network data structure NET, together with
+%	input and target data matrices X and T, and compares the evaluation
+%	of the Hessian matrix using the function NETHESS and using central
+%	differences with the function NETERR.
+%
+%	The optional return value H is the Hessian computed using NETHESS.
+%
+%	See also
+%	NETHESS, NETERR
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+w0 = netpak(net);
+nwts = length(w0);
+h = nethess(w0, net, x, t);
+
+w = w0;
+hcent = zeros(nwts, nwts);
+h1 =  0.0; h2 =  0.0; h3 =  0.0; h4 = 0.0;
+epsilon = 1.0e-4;
+fprintf(1, 'Checking Hessian ...\n\n');
+for k = 1:nwts;
+  for l = 1:nwts;
+    if(l == k)
+      w(k) = w0(k) + 2.0*epsilon;
+      h1 = neterr(w, net, x, t);
+      w(k) = w0(k) - 2.0*epsilon;
+      h2 = neterr(w, net, x, t);
+      w(k) = w0(k);
+      h3 = neterr(w, net, x, t);
+      hcent(k, k) = (h1 + h2 - 2.0*h3)/(4.0*epsilon^2);
+    else
+      w(k) = w0(k) + epsilon;
+      w(l) = w0(l) + epsilon;
+      h1 = neterr(w, net, x, t);
+      w(k) = w0(k) - epsilon;
+      w(l) = w0(l) - epsilon;
+      h2 = neterr(w, net, x, t);
+      w(k) = w0(k) + epsilon;
+      w(l) = w0(l) - epsilon;
+      h3 = neterr(w, net, x, t);
+      w(k) = w0(k) - epsilon;
+      w(l) = w0(l) + epsilon;
+      h4 = neterr(w, net, x, t);
+      hcent(k, l) = (h1 + h2 - h3 - h4)/(4.0*epsilon^2);
+      w(k) = w0(k);
+      w(l) = w0(l);
+    end
+  end
+end
+
+fprintf(1, '   analytical    numerical       delta\n\n');
+temp = [h(:), hcent(:), (h(:) - hcent(:))];
+fprintf(1, '%12.6f  %12.6f  %12.6f\n', temp');
\ No newline at end of file