diff toolboxes/FullBNT-1.0.7/netlabKPM/kmeans_demo.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/netlabKPM/kmeans_demo.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,76 @@
+function kmeans_demo()
+
+% Generate T points from K=5 1D clusters, and try to recover the cluster
+% centers using k-means.
+% Requires BNT, netlab and the matlab stats toolbox v4.
+
+K = 5;
+ndim = 1;
+true_centers = 1:K;
+sigma = 1e-6;
+T = 100;
+% data(t,:) is the t'th data point
+data = zeros(T, ndim); 
+% ndx(t) = i means the t'th data point is sample from cluster i
+%ndx = sample_discrete(normalise(ones(1,K)));
+ndx = [1*ones(1,20) 2*ones(1,20) 3*ones(1,20) 4*ones(1,20) 5*ones(1,20)];
+for t=1:T
+  data(t) = sample_gaussian(true_centers(ndx(t)), sigma, 1);
+end
+plot(1:T, data, 'x')
+
+
+
+% set the centers randomly from Gauss(0)
+mix = gmm(ndim, K, 'spherical');
+h = plot_centers_as_lines(mix, [], T);
+
+if 0
+% Place initial centers at K data points chosen at random, but add some noise
+choose_ndx = randperm(T);
+choose_ndx = choose_ndx(1:K);
+init_centers = data(choose_ndx) + sample_gaussian(0, 0.1, K);
+mix.centres = init_centers;
+h = plot_centers_as_lines(mix, h, T);
+end
+
+if 0
+% update centers using netlab k-means
+options = foptions;
+niter = 10;
+options(14) = niter;
+mix = gmminit(mix, data, options);
+h = plot_centers_as_lines(mix, h, T);
+end
+
+% use matlab stats toolbox k-means with multiple restarts
+nrestarts = 5;
+[idx, centers] = kmeans(data, K, 'replicates', nrestarts, ...
+			'emptyAction', 'singleton', 'display', 'iter');
+mix.centres = centers;
+h = plot_centers_as_lines(mix, h, T);
+
+% fine tune with EM; compute covariances of each cluster
+options = foptions;
+niter = 20;
+options(1) = 1; % display cost fn at each iter
+options(14) = niter;
+mix = gmmem(mix, data, options);
+h = plot_centers_as_lines(mix, h, T);
+
+%%%%%%%%%
+function h = plot_centers_as_lines(mix, h, T)
+
+K = mix.ncentres;
+hold on
+if isempty(h)
+  for k=1:K
+    h(k)=line([0 T], [mix.centres(k) mix.centres(k)]);
+  end
+else
+  for k=1:K
+    set(h(k), 'xdata', [0 T], 'ydata', [mix.centres(k) mix.centres(k)]);
+  end
+end
+hold off
+