Mercurial > hg > camir-aes2014
annotate toolboxes/FullBNT-1.0.7/bnt/examples/static/StructLearn/cooper_yoo.m @ 0:e9a9cd732c1e tip
first hg version after svn
| author | wolffd |
|---|---|
| date | Tue, 10 Feb 2015 15:05:51 +0000 |
| parents | |
| children |
| rev | line source |
|---|---|
| wolffd@0 | 1 % Do the example in Cooper and Yoo, "Causal discovery from a mixture of experimental and |
| wolffd@0 | 2 % observational data", UAI 99, p120 |
| wolffd@0 | 3 |
| wolffd@0 | 4 N = 2; |
| wolffd@0 | 5 dag = zeros(N); |
| wolffd@0 | 6 A = 1; B = 2; |
| wolffd@0 | 7 dag(A,B) = 1; |
| wolffd@0 | 8 ns = 2*ones(1,N); |
| wolffd@0 | 9 |
| wolffd@0 | 10 bnet0 = mk_bnet(dag, ns); |
| wolffd@0 | 11 %bnet0.CPD{A} = tabular_CPD(bnet0, A, 'unif', 1); |
| wolffd@0 | 12 bnet0.CPD{A} = tabular_CPD(bnet0, A, 'CPT', 'unif', 'prior_type', 'dirichlet'); |
| wolffd@0 | 13 bnet0.CPD{B} = tabular_CPD(bnet0, B, 'CPT', 'unif', 'prior_type', 'dirichlet'); |
| wolffd@0 | 14 |
| wolffd@0 | 15 samples = [2 2; |
| wolffd@0 | 16 2 1; |
| wolffd@0 | 17 2 2; |
| wolffd@0 | 18 1 1; |
| wolffd@0 | 19 1 2; |
| wolffd@0 | 20 2 2; |
| wolffd@0 | 21 1 1; |
| wolffd@0 | 22 2 2; |
| wolffd@0 | 23 1 2; |
| wolffd@0 | 24 2 1; |
| wolffd@0 | 25 1 1]; |
| wolffd@0 | 26 |
| wolffd@0 | 27 clamped = [0 0; |
| wolffd@0 | 28 0 0; |
| wolffd@0 | 29 0 0; |
| wolffd@0 | 30 0 0; |
| wolffd@0 | 31 0 0; |
| wolffd@0 | 32 1 0; |
| wolffd@0 | 33 1 0; |
| wolffd@0 | 34 0 1; |
| wolffd@0 | 35 0 1; |
| wolffd@0 | 36 0 1; |
| wolffd@0 | 37 0 1]; |
| wolffd@0 | 38 |
| wolffd@0 | 39 nsamples = size(samples, 1); |
| wolffd@0 | 40 |
| wolffd@0 | 41 % sequential version |
| wolffd@0 | 42 LL = 0; |
| wolffd@0 | 43 bnet = bnet0; |
| wolffd@0 | 44 for l=1:nsamples |
| wolffd@0 | 45 ev = num2cell(samples(l,:)'); |
| wolffd@0 | 46 manip = find(clamped(l,:)'); |
| wolffd@0 | 47 LL = LL + log_marg_lik_complete(bnet, ev, manip); |
| wolffd@0 | 48 bnet = bayes_update_params(bnet, ev, manip); |
| wolffd@0 | 49 end |
| wolffd@0 | 50 assert(approxeq(exp(LL), 5.97e-7)) % compare with result from UAI paper |
| wolffd@0 | 51 |
| wolffd@0 | 52 |
| wolffd@0 | 53 % batch version |
| wolffd@0 | 54 cases = num2cell(samples'); |
| wolffd@0 | 55 LL2 = log_marg_lik_complete(bnet0, cases, clamped'); |
| wolffd@0 | 56 bnet2 = bayes_update_params(bnet0, cases, clamped'); |
| wolffd@0 | 57 |
| wolffd@0 | 58 assert(approxeq(LL, LL2)) |
| wolffd@0 | 59 |
| wolffd@0 | 60 for j=1:N |
| wolffd@0 | 61 s1 = struct(bnet.CPD{j}); % violate object privacy |
| wolffd@0 | 62 s2 = struct(bnet2.CPD{j}); |
| wolffd@0 | 63 assert(approxeq(s1.CPT, s2.CPT)) |
| wolffd@0 | 64 end |
| wolffd@0 | 65 |