diff toolboxes/FullBNT-1.0.7/bnt/examples/static/StructLearn/bic1.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/bnt/examples/static/StructLearn/bic1.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,79 @@
+% compare BIC and Bayesian score 
+
+N = 4;
+dag = zeros(N,N);
+%C = 1; S = 2; R = 3; W = 4; % topological order
+C = 4; S = 2; R = 3; W = 1; % arbitrary order
+dag(C,[R S]) = 1;
+dag(R,W) = 1;
+dag(S,W)=1;
+
+
+false = 1; true = 2;
+ns = 2*ones(1,N); % binary nodes
+bnet = mk_bnet(dag, ns);
+bnet.CPD{C} = tabular_CPD(bnet, C, 'CPT', [0.5 0.5]);
+bnet.CPD{R} = tabular_CPD(bnet, R, 'CPT', [0.8 0.2 0.2 0.8]);
+bnet.CPD{S} = tabular_CPD(bnet, S, 'CPT', [0.5 0.9 0.5 0.1]);
+bnet.CPD{W} = tabular_CPD(bnet, W, 'CPT', [1 0.1 0.1 0.01 0 0.9 0.9 0.99]);
+
+
+seed = 0;
+rand('state', seed);
+randn('state', seed);
+ncases = 1000;
+data = cell(N, ncases);
+for m=1:ncases
+  data(:,m) = sample_bnet(bnet);
+end
+
+priors = [0.1 1 10];
+P = length(priors);
+params = cell(1,P);
+for p=1:P
+  params{p} = cell(1,N);
+  for i=1:N
+    %params{p}{i} = {'prior', priors(p)};
+    params{p}{i} = {'prior_type', 'dirichlet', 'dirichlet_weight', priors(p)};
+  end
+end
+
+%sz = 1000:1000:10000;
+sz = 10:10:100;
+S = length(sz);
+bic_score = zeros(S, 1);
+bayes_score = zeros(S, P);
+for i=1:S
+  bic_score(i) = score_dags(data(:,1:sz(i)), ns, {dag}, 'scoring_fn', 'bic', 'params', []);
+end
+diff = zeros(S,P);
+for p=1:P
+  for i=1:S
+    bayes_score(i,p) = score_dags(data(:,1:sz(i)), ns, {dag}, 'params', params{p});
+  end
+end
+
+for p=1:P
+  for i=1:S
+    diff(i,p) = bayes_score(i,p)/ bic_score(i);
+    %diff(i,p) = abs(bayes_score(i,p) - bic_score(i));
+  end
+end
+
+if 0
+plot(sz, diff(:,1), 'g--*', sz, diff(:,2), 'b-.+', sz, diff(:,3), 'k:s');
+title('Relative BIC error vs. size of data set')
+legend('BDeu 0.1', 'BDeu 1', 'Bdeu 10', 2)
+end
+
+if 0
+plot(sz, bic_score, 'r-o',  sz, bayes_score(:,1), 'g--*', sz, bayes_score(:,2), 'b-.+', sz, bayes_score(:,3), 'k:s');
+legend('bic', 'BDeu 0.01', 'BDeu 1', 'Bdeu 100')
+ylabel('score')
+title('score vs. size of data set')
+end
+
+%xlabel('num. data cases')
+
+%previewfig(gcf, 'format', 'png', 'height', 2, 'color', 'rgb')
+%exportfig(gcf, '/home/cs/murphyk/public_html/Bayes/Figures/bic.png', 'format', 'png', 'height', 2, 'color', 'rgb')