Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/bnt/examples/static/gaussian2.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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-1:000000000000 | 0:e9a9cd732c1e |
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1 % Make the following network (from Jensen (1996) p84 fig 4.17) | |
2 % 1 | |
3 % / | \ | |
4 % 2 3 4 | |
5 % | | | | |
6 % 5 6 7 | |
7 % \/ \/ | |
8 % 8 9 | |
9 % where all arcs point downwards | |
10 | |
11 | |
12 N = 9; | |
13 dag = zeros(N,N); | |
14 dag(1,2)=1; dag(1,3)=1; dag(1,4)=1; | |
15 dag(2,5)=1; dag(3,6)=1; dag(4,7)=1; | |
16 dag(5,8)=1; dag(6,8)=1; dag(6,9)=1; dag(7,9) = 1; | |
17 | |
18 ns = [5 4 3 2 2 1 2 2 2]; % vector-valued nodes | |
19 %ns = ones(1,9); % scalar nodes | |
20 dnodes = []; | |
21 | |
22 bnet = mk_bnet(dag, ns, 'discrete', []); | |
23 rand('state', 0); | |
24 randn('state', 0); | |
25 for i=1:N | |
26 bnet.CPD{i} = gaussian_CPD(bnet, i); | |
27 end | |
28 | |
29 clear engine; | |
30 engine{1} = gaussian_inf_engine(bnet); | |
31 engine{2} = jtree_inf_engine(bnet); | |
32 | |
33 [err, time] = cmp_inference_static(bnet, engine); | |
34 | |
35 Nsamples = 100; | |
36 samples = cell(N, Nsamples); | |
37 for s=1:Nsamples | |
38 samples(:,s) = sample_bnet(bnet); | |
39 end | |
40 bnet2 = learn_params(bnet, samples); |