Daniel@0: function plot_mixexp(theta, eta, data)
Daniel@0: % PLOT_MIXEXP  Plot the results for a piecewise linear regression model
Daniel@0: % plot_mixexp(theta, eta, data)
Daniel@0: % 
Daniel@0: % data(l,:) = [x y] for example l
Daniel@0: % theta(i,:) = regression vector for expert i
Daniel@0: % eta(i,:) = softmax (gating) params for expert i
Daniel@0: 
Daniel@0: numexp = size(theta, 1);
Daniel@0: 
Daniel@0: mn = min(data);
Daniel@0: mx = max(data);
Daniel@0: xa = mn(1):0.01:mx(1);
Daniel@0: x = [ones(length(xa),1) xa'];
Daniel@0: % pr(i,l) = posterior probability of expert i on example l
Daniel@0: pr = exp(eta * x');
Daniel@0: pr = pr ./ (ones(numexp,1) * sum(pr));
Daniel@0: % y(i,l) = prediction of expert i for example l
Daniel@0: y = theta * x';
Daniel@0: % yg(l) = weighted prediction  for example l
Daniel@0: yg = sum(y .* pr)';
Daniel@0: 
Daniel@0: subplot(3,2,1);
Daniel@0: plot(xa, y(1,:));
Daniel@0: title('expert 1');
Daniel@0: 
Daniel@0: subplot(3,2,2);
Daniel@0: plot(xa, y(2,:));
Daniel@0: title('expert 2');
Daniel@0: 
Daniel@0: subplot(3,2,3);
Daniel@0: plot(xa, pr(1,:));
Daniel@0: title('gating 1');
Daniel@0: 
Daniel@0: subplot(3,2,4);
Daniel@0: plot(xa, pr(2,:));
Daniel@0: title('gating 2');
Daniel@0: 
Daniel@0: subplot(3,2,5);
Daniel@0: plot(xa, yg);
Daniel@0: axis([-1 1 -1 2])
Daniel@0: title('prediction');
Daniel@0: 
Daniel@0: subplot(3,2,6);
Daniel@0: title('data');
Daniel@0: hold on
Daniel@0: plot(data(:,1), data(:,2), '+');
Daniel@0: hold off
Daniel@0: