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/BNT/examples/static/Misc/mixexp_plot.m b/sourcecodes/bnt-master/BNT/examples/static/Misc/mixexp_plot.m
new file mode 100644
index 00000000..bb2a2fec
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/examples/static/Misc/mixexp_plot.m
@@ -0,0 +1,49 @@
+function plot_mixexp(theta, eta, data)
+% PLOT_MIXEXP  Plot the results for a piecewise linear regression model
+% plot_mixexp(theta, eta, data)
+% 
+% data(l,:) = [x y] for example l
+% theta(i,:) = regression vector for expert i
+% eta(i,:) = softmax (gating) params for expert i
+
+numexp = size(theta, 1);
+
+mn = min(data);
+mx = max(data);
+xa = mn(1):0.01:mx(1);
+x = [ones(length(xa),1) xa'];
+% pr(i,l) = posterior probability of expert i on example l
+pr = exp(eta * x');
+pr = pr ./ (ones(numexp,1) * sum(pr));
+% y(i,l) = prediction of expert i for example l
+y = theta * x';
+% yg(l) = weighted prediction  for example l
+yg = sum(y .* pr)';
+
+subplot(3,2,1);
+plot(xa, y(1,:));
+title('expert 1');
+
+subplot(3,2,2);
+plot(xa, y(2,:));
+title('expert 2');
+
+subplot(3,2,3);
+plot(xa, pr(1,:));
+title('gating 1');
+
+subplot(3,2,4);
+plot(xa, pr(2,:));
+title('gating 2');
+
+subplot(3,2,5);
+plot(xa, yg);
+axis([-1 1 -1 2])
+title('prediction');
+
+subplot(3,2,6);
+title('data');
+hold on
+plot(data(:,1), data(:,2), '+');
+hold off
+