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1 % Computing most probable explanation.
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2
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3 % If you don't break ties consistently, loopy can give wrong mpe
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4 % even though the graph has no cycles, and even though the max-marginals are the same.
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5 % This example was contributed by Wentau Yih <wtyih@yahoo.com> 29 Jan 02.
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6
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7 % define loop-free graph structure (all edges point down)
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8 %
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9 % Xe1 Xe2
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10 % | |
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11 % E1 E2
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12 % \ /
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13 % R1
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14 % |
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15 % Xr1
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16
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17 N = 6;
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18 dag = zeros(N,N);
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19 Xe1 = 1; Xe2 = 2; E1 = 3; E2 = 4; R1 = 5; Xr1 = 6;
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20 dag(Xe1, E1) = 1;
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21 dag(Xe2, E2) = 1;
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22 dag([E1 E2], R1) = 1;
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23 dag(R1, Xr1) = 1;
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24
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25 node_sizes = [ 1 1 2 2 2 1 ];
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26
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27 % create BN
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28
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29 bnet = mk_bnet(dag, node_sizes, 'observed', [Xe1 Xe2 Xr1]);
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30
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31 % fill in CPT
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32
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33 bnet.CPD{Xe1} = tabular_CPD(bnet, Xe1, [1]);
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34 bnet.CPD{Xe2} = tabular_CPD(bnet, Xe2, [1]);
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35 bnet.CPD{E1} = tabular_CPD(bnet, E1, [0.2 0.8]);
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36 bnet.CPD{E2} = tabular_CPD(bnet, E2, [0.3 0.7]);
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37 bnet.CPD{R1} = tabular_CPD(bnet, R1, [1 1 1 0.8 0 0 0 0.2]);
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38 bnet.CPD{Xr1} = tabular_CPD(bnet, Xr1, [0.15 0.85]);
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39
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40 clear engine;
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41 engine{1} = belprop_inf_engine(bnet);
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42 engine{2} = jtree_inf_engine(bnet);
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43 engine{3} = global_joint_inf_engine(bnet);
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44 engine{4} = var_elim_inf_engine(bnet);
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45
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46 evidence = cell(1,N);
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47 evidence{Xe1} = 1; evidence{Xe2} = 1; evidence{Xr1} = 1;
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48
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49 mpe = find_mpe(engine{1}, evidence, 'break_ties', 0) % gives wrong results
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50 mpe = find_mpe(engine{1}, evidence)
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51 for i=2:4
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52 mpe = find_mpe(engine{i}, evidence)
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53 end
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