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

first hg version after svn

+% Example of explaining away from
+% http://www.ai.mit.edu/~murphyk/Bayes/bnintro.html#explainaway
+%
+% Suppose you have to be brainy or smart to get into college.
+% B S P(C=1) P(C=2)  1=false 2=true
+% 1 1 1.0    0.0 
+% 2 1 0.0    1.0
+% 1 2 0.0    1.0
+% 2 2 0.0    1.0
+%
+%
+% If we observe that you are in college, you must be either brainy or sporty or both.
+% If we observre you are in college and sporty, it is less likely you are brainy, 
+% since brainy-ness and sporty-ness compete as causal explanations of the effect.
+
+% B  S
+%  \/
+%   C
+
+B = 1; S = 2; C = 3;
+dag = zeros(3,3);
+dag([B S], C)=1;
+ns = 2*ones(1,3);
+bnet = mk_bnet(dag, ns);
+bnet.CPD{B} = tabular_CPD(bnet, B, 'CPT', [0.5 0.5]');
+bnet.CPD{S} = tabular_CPD(bnet, S, 'CPT', [0.5 0.5]');
+CPT = zeros(2,2,2);
+CPT(1,1,:) = [1 0];
+CPT(2,1,:) = [0 1];
+CPT(1,2,:) = [0 1];
+CPT(2,2,:) = [0 1];
+bnet.CPD{C} = tabular_CPD(bnet, C, 'CPT', CPT);
+
+engine = jtree_inf_engine(bnet);
+ev = cell(1,3);
+ev{C} = 2;
+engine = enter_evidence(engine, ev);
+m = marginal_nodes(engine, B);
+fprintf('P(B=true|C=true) = %5.3f\n', m.T(2)) % 0.67
+
+ev{S} = 2;
+engine = enter_evidence(engine, ev);
+m = marginal_nodes(engine, B);
+fprintf('P(B=true|C=true,S=true) = %5.3f\n', m.T(2)) % 0.5 = unconditional baseline P(B=true)