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annotate toolboxes/FullBNT-1.0.7/bnt/examples/static/Brutti/Belief_hme.m @ 0:e9a9cd732c1e tip

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first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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wolffd@0 1 % Sigmoid Belief Hierarchical Mixtures of Experts
wolffd@0 2
wolffd@0 3 clear all
wolffd@0 4 clc
wolffd@0 5 X = 1;
wolffd@0 6 Q1 = 2;
wolffd@0 7 Q2 = 3;
wolffd@0 8 Y = 4;
wolffd@0 9 dag = zeros(4,4);
wolffd@0 10 dag(X,[Q1 Q2 Y]) = 1;
wolffd@0 11 dag(Q1, [Q2 Y]) = 1;
wolffd@0 12 dag(Q2,Y)=1;
wolffd@0 13 ns = [1 3 4 3];
wolffd@0 14 dnodes = [2 3 4];
wolffd@0 15 onodes=[1 2 3 4];
wolffd@0 16 bnet = mk_bnet(dag,ns, dnodes);
wolffd@0 17
wolffd@0 18 rand('state',0); randn('state',0);
wolffd@0 19
wolffd@0 20 bnet.CPD{1} = root_CPD(bnet, 1);
wolffd@0 21 bnet.CPD{2} = softmax_CPD(bnet, 2, 'max_iter', 3);
wolffd@0 22 bnet.CPD{3} = softmax_CPD(bnet, 3, 'discrete', [2], 'max_iter', 3);
wolffd@0 23 bnet.CPD{4} = softmax_CPD(bnet, 4, 'discrete', [2 3], 'max_iter', 3);
wolffd@0 24
wolffd@0 25 T=5;
wolffd@0 26 cases = cell(4, T);
wolffd@0 27 cases(1,:)=num2cell(rand(1,T));
wolffd@0 28 %cases(2,:)=num2cell(round(rand(1,T)*2)+1);
wolffd@0 29 %cases(3,:)=num2cell(round(rand(1,T)*3)+1);
wolffd@0 30 cases(4,:)=num2cell(round(rand(1,T)*2)+1);
wolffd@0 31
wolffd@0 32 engine = jtree_inf_engine(bnet, onodes);
wolffd@0 33
wolffd@0 34 [engine, loglik] = enter_evidence(engine, cases);
wolffd@0 35
wolffd@0 36 disp('learning-------------------------------------------')
wolffd@0 37 [bnet2, LL2] = learn_params_em(engine, cases, 4);