comparison toolboxes/FullBNT-1.0.7/bnt/examples/static/lw1.m @ 0:e9a9cd732c1e tip

first hg version after svn

+% Evaluate effectiveness of likelihood weighting on the lawn sprinkler example
+
+N = 4; 
+dag = zeros(N,N);
+C = 1; R = 2; S = 3; W = 4;
+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, [0.5 0.5]);
+bnet.CPD{R} = tabular_CPD(bnet, R, [0.8 0.2 0.2 0.8]);
+bnet.CPD{S} = tabular_CPD(bnet, S, [0.5 0.9 0.5 0.1]);
+bnet.CPD{W} = tabular_CPD(bnet, W, [1 0.1 0.1 0.01 0 0.9 0.9 0.99]);
+
+
+clear engine;
+engine{1} = jtree_inf_engine(bnet);
+engine{2} = likelihood_weighting_inf_engine(bnet);
+
+nengines = length(engine);
+m = cell(1, nengines);
+ll = zeros(1, nengines);
+
+evidence = cell(1,N);
+%evidence{C} = true; % evidence at the top is the easiest
+evidence{W} = true; % evidence at the bottom is the hardets
+
+query = [R];
+
+i=1;
+engine{i}  = enter_evidence(engine{i}, evidence);
+exact_m = marginal_nodes(engine{i}, query);
+
+i=2;
+samples = 100:100:500;
+err = zeros(1, length(samples));
+for j=1:length(samples)
+  nsamples = samples(j);
+  engine{i}  = enter_evidence(engine{i}, evidence, nsamples);
+  approx_m = marginal_nodes(engine{i}, query);
+  a1=approxeq(approx_m.T,exact_m.T,1e-1);
+  a2=approxeq(approx_m.T,exact_m.T,1e-2);
+  a3=approxeq(approx_m.T,exact_m.T,1e-3);
+  e = sum(abs(approx_m.T(:) - exact_m.T(:)));
+  fprintf('%d samples, 1dp %d, 2dp %d, 3dp %d,  err %f\n', nsamples, a1, a2, a3, e);
+  err(j) = e;
+end