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, 51 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/netlab3.3/mlphess.m b/sourcecodes/bnt-master/netlab3.3/mlphess.m
new file mode 100644
index 00000000..bd7c44e9
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+++ b/sourcecodes/bnt-master/netlab3.3/mlphess.m
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+function [h, hdata] = mlphess(net, x, t, hdata)
+%MLPHESS Evaluate the Hessian matrix for a multi-layer perceptron network.
+%
+%	Description
+%	H = MLPHESS(NET, X, T) takes an MLP network data structure NET, a
+%	matrix X of input values, and a matrix T of target values and returns
+%	the full Hessian matrix H corresponding to the second derivatives of
+%	the negative log posterior distribution, evaluated for the current
+%	weight and bias values as defined by NET.
+%
+%	[H, HDATA] = MLPHESS(NET, X, T) returns both the Hessian matrix H and
+%	the contribution HDATA arising from the data dependent term in the
+%	Hessian.
+%
+%	H = MLPHESS(NET, X, T, HDATA) takes a network data structure NET, a
+%	matrix X of input values, and a matrix T of  target values, together
+%	with the contribution HDATA arising from the data dependent term in
+%	the Hessian, and returns the full Hessian matrix H corresponding to
+%	the second derivatives of the negative log posterior distribution.
+%	This version saves computation time if HDATA has already been
+%	evaluated for the current weight and bias values.
+%
+%	See also
+%	MLP, HESSCHEK, MLPHDOTV, EVIDENCE
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% Check arguments for consistency
+errstring = consist(net, 'mlp', x, t);
+if ~isempty(errstring);
+  error(errstring);
+end
+
+if nargin == 3
+  % Data term in Hessian needs to be computed
+  hdata = datahess(net, x, t);
+end
+
+[h, hdata] = hbayes(net, hdata);
+
+% Sub-function to compute data part of Hessian
+function hdata = datahess(net, x, t)
+
+hdata = zeros(net.nwts, net.nwts);
+
+for v = eye(net.nwts);
+  hdata(find(v),:) = mlphdotv(net, x, t, v);
+end
+
+return