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authorziejd22017-09-28 15:04:40 -0500
committerziejd22017-09-28 15:04:40 -0500
commit8070dc963753142bb86c4ed698d91fd623ed28e7 (patch)
treed0f6dd8fc46a49b819aa55c1a90faa14d8448883 /sourcecodes/bnt-master/netlab3.3/mlppak.m
parent7cc31810d53176e805532b2789955f4eedbce6bb (diff)
downloadBNW-8070dc963753142bb86c4ed698d91fd623ed28e7.tar.gz
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
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+function w = mlppak(net)
+%MLPPAK	Combines weights and biases into one weights vector.
+%
+%	Description
+%	W = MLPPAK(NET) takes a network data structure NET and combines the
+%	component weight matrices bias vectors into a single row vector W.
+%	The facility to switch between these two representations for the
+%	network parameters is useful, for example, in training a network by
+%	error function minimization, since a single vector of parameters can
+%	be handled by general-purpose optimization routines.
+%
+%	The ordering of the paramters in W is defined by
+%	  w = [net.w1(:)', net.b1, net.w2(:)', net.b2];
+%	 where W1 is the first-layer weight matrix, B1 is the first-layer
+%	bias vector, W2 is the second-layer weight matrix, and B2 is the
+%	second-layer bias vector.
+%
+%	See also
+%	MLP, MLPUNPAK, MLPFWD, MLPERR, MLPBKP, MLPGRAD
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+% Check arguments for consistency
+errstring = consist(net, 'mlp');
+if ~isempty(errstring);
+  error(errstring);
+end
+
+w = [net.w1(:)', net.b1, net.w2(:)', net.b2];
+