wolffd@0
|
1 function bnet = mk_qmr_bnet(G, inhibit, leak, prior, tabular_findings, onodes)
|
wolffd@0
|
2 % MK_QMR_BNET Make a QMR model
|
wolffd@0
|
3 % bnet = mk_qmr_bnet(G, inhibit, leak, prior)
|
wolffd@0
|
4 %
|
wolffd@0
|
5 % G(i,j) = 1 iff there is an arc from disease i to finding j
|
wolffd@0
|
6 % inhibit(i,j) = inhibition probability on i->j arc
|
wolffd@0
|
7 % leak(j) = inhibition prob. on leak->j arc
|
wolffd@0
|
8 % prior(i) = prob. disease i is on
|
wolffd@0
|
9 % tabular_findings = 1 means multinomial leaves (ignores leak/inhibit params)
|
wolffd@0
|
10 % = 0 means noisy-OR leaves (default = 0)
|
wolffd@0
|
11
|
wolffd@0
|
12 if nargin < 5, tabular_findings = 0; end
|
wolffd@0
|
13
|
wolffd@0
|
14 [Ndiseases Nfindings] = size(inhibit);
|
wolffd@0
|
15 N = Ndiseases + Nfindings;
|
wolffd@0
|
16 finding_node = Ndiseases+1:N;
|
wolffd@0
|
17 ns = 2*ones(1,N);
|
wolffd@0
|
18 dag = zeros(N,N);
|
wolffd@0
|
19 dag(1:Ndiseases, finding_node) = G;
|
wolffd@0
|
20 if nargin < 6, onodes = finding_node; end
|
wolffd@0
|
21 bnet = mk_bnet(dag, ns, 'observed', onodes);
|
wolffd@0
|
22
|
wolffd@0
|
23 for d=1:Ndiseases
|
wolffd@0
|
24 CPT = [1-prior(d) prior(d)];
|
wolffd@0
|
25 bnet.CPD{d} = tabular_CPD(bnet, d, CPT');
|
wolffd@0
|
26 end
|
wolffd@0
|
27
|
wolffd@0
|
28 for i=1:Nfindings
|
wolffd@0
|
29 fnode = finding_node(i);
|
wolffd@0
|
30 ps = parents(G, i);
|
wolffd@0
|
31 if tabular_findings
|
wolffd@0
|
32 bnet.CPD{fnode} = tabular_CPD(bnet, fnode);
|
wolffd@0
|
33 else
|
wolffd@0
|
34 bnet.CPD{fnode} = noisyor_CPD(bnet, fnode, leak(i), inhibit(ps, i));
|
wolffd@0
|
35 end
|
wolffd@0
|
36 end
|
wolffd@0
|
37
|
wolffd@0
|
38
|
wolffd@0
|
39
|
wolffd@0
|
40
|
wolffd@0
|
41
|