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

first hg version after svn

+function demhint(nin, nhidden, nout)
+%DEMHINT Demonstration of Hinton diagram for 2-layer feed-forward network.
+%
+%	Description
+%
+%	DEMHINT plots a Hinton diagram for a 2-layer feedforward network with
+%	5 inputs, 4 hidden units and 3 outputs. The weight vector is chosen
+%	from a Gaussian distribution as described under MLP.
+%
+%	DEMHINT(NIN, NHIDDEN, NOUT) allows the user to specify the number of
+%	inputs, hidden units and outputs.
+%
+%	See also
+%	HINTON, HINTMAT, MLP, MLPPAK, MLPUNPAK
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+if nargin < 1 nin = 5; end
+if nargin < 2 nhidden = 7; end
+if nargin < 3 nout = 3; end
+
+% Fix the seed for reproducible results
+randn('state', 42);
+clc
+disp('This demonstration illustrates the plotting of Hinton diagrams')
+disp('for Multi-Layer Perceptron networks.')
+disp(' ')
+disp('Press any key to continue.')
+pause
+net = mlp(nin, nhidden, nout, 'linear');
+
+[h1, h2] = mlphint(net);
+clc
+disp('The MLP has been created with')
+disp(['    ' int2str(nin) ' inputs'])
+disp(['    ' int2str(nhidden) ' hidden units'])
+disp(['    ' int2str(nout) ' outputs'])
+disp(' ')
+disp('One figure is produced for each layer of weights.')
+disp('For each layer the fan-in weights are arranged in rows for each unit.')
+disp('The bias weight is separated from the rest by a red vertical line.')
+disp('The area of each box is proportional to the weight value: positive')
+disp('values are white, and negative are black.')
+disp(' ')
+disp('Press any key to exit.'); 
+pause; 
+delete(h1);
+delete(h2);