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1 % Compare various inference engines on the following network (from Jensen (1996) p84 fig 4.17)
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2 % 1
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3 % / | \
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4 % 2 3 4
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5 % | | |
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6 % 5 6 7
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7 % \/ \/
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8 % 8 9
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9 % where all arcs point downwards
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10 seed = 0;
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11 rand('state', seed);
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12 randn('state', seed);
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13
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14 N = 9;
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15 dag = zeros(N,N);
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16 dag(1,2)=1; dag(1,3)=1; dag(1,4)=1;
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17 dag(2,5)=1; dag(3,6)=1; dag(4,7)=1;
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18 dag(5,8)=1; dag(6,8)=1; dag(6,9)=1; dag(7,9) = 1;
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19
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20 dnodes = 1:N;
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21 false = 1; true = 2;
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22 ns = 2*ones(1,N); % binary nodes
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23
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24 onodes = [2 4];
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25 bnet = mk_bnet(dag, ns, 'observed', onodes);
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26 % use random params
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27 for i=1:N
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28 bnet.CPD{i} = tabular_CPD(bnet, i);
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29 end
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30
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31 %USEC = exist('@jtree_C_inf_engine/collect_evidence','file');
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32 query = [3];
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33 engine = {};
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34 engine{end+1} = jtree_inf_engine(bnet);
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35 engine{end+1} = jtree_sparse_inf_engine(bnet);
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36 %engine{end+1} = jtree_ndx_inf_engine(bnet, 'ndx_type', 'SD');
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37 %engine{end+1} = jtree_ndx_inf_engine(bnet, 'ndx_type', 'B');
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38 %engine{end+1} = jtree_ndx_inf_engine(bnet, 'ndx_type', 'D');
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39 %if USEC, engine{end+1} = jtree_C_inf_engine(bnet); end
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40 %engine{end+1} = var_elim_inf_engine(bnet);
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41 %engine{end+1} = enumerative_inf_engine(bnet);
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42 %engine{end+1} = jtree_onepass_inf_engine(bnet, query, onodes);
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43
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44 maximize = 0; % jtree_ndx crashes on max-prop
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45 [err, time] = cmp_inference_static(bnet, engine, 'maximize', maximize);
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46
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