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1 function T = convert_to_table(CPD, domain, evidence)
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2 % CONVERT_TO_TABLE Convert a mlp CPD to a table, incorporating any evidence
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3 % T = convert_to_table(CPD, domain, evidence)
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4
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5 self = domain(end);
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6 ps = domain(1:end-1); % self' parents
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7 %cps = myintersect(ps, cnodes); % self' continous parents
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8 cnodes = domain(CPD.cpndx);
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9 cps = myintersect(ps, cnodes);
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10 odom = domain(~isemptycell(evidence(domain))); % obs nodes in the net
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11 assert(myismember(cps, odom)); % !ALL the CTS parents must be observed!
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12 ns(cps)=1;
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13 dps = mysetdiff(ps, cps); % self' discrete parents
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14 dobs = myintersect(dps, odom); % discrete obs parents
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15
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16 % Extract the params compatible with the observations (if any) on the discrete parents (if any)
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17
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18 if ~isempty(dobs),
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19 dvals = cat(1, evidence{dobs});
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20 ns_eff= CPD.sizes; % effective node sizes
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21 ens=ns_eff;
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22 ens(dobs) = 1;
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23 S=prod(ens(dps));
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24 subs = ind2subv(ens(dps), 1:S);
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25 mask = find_equiv_posns(dobs, dps);
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26 for i=1:length(mask),
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27 subs(:,mask(i)) = dvals(i);
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28 end
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29 support = subv2ind(ns_eff(dps), subs)';
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30 else
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31 ns_eff= CPD.sizes;
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32 support=[1:prod(ns_eff(dps))];
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33 end
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34
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35 W1=[]; b1=[]; W2=[]; b2=[];
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36
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37 W1 = CPD.W1(:,:,support);
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38 b1= CPD.b1(support,:);
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39 W2 = CPD.W2(:,:,support);
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40 b2= CPD.b2(support,:);
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41 ns(odom) = 1;
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42 dpsize = prod(ns(dps)); % overall size of the self' discrete parents
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43
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44 x = cat(1, evidence{cps});
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45 ndata=size(x,2);
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46
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47 if ~isempty(evidence{self}) %
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48 app=struct(CPD); %
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49 ns(self)=app.mlp{1}.nout; % pump up self to the original dimension if observed
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50 clear app; %
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51 end %
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52
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53 T =zeros(dpsize, ns(self)); %
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54 for i=1:dpsize %
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55 W1app = W1(:,:,i); %
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56 b1app = b1(i,:); %
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57 W2app = W2(:,:,i); %
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58 b2app = b2(i,:); % for each of the dpsize combinations of self'parents values
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59 z = tanh(x(:)'*W1app + ones(ndata, 1)*b1app); % we tabulate the corrisponding glm model
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60 a = z*W2app + ones(ndata, 1)*b2app; % (element of the cell array CPD.glim)
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61 appoggio = normalise(exp(a)); %
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62 T(i,:)=appoggio; %
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63 W1app=[]; W2app=[]; b1app=[]; b2app=[]; %
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64 z=[]; a=[]; appoggio=[]; %
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65 end %
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66
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67 if ~isempty(evidence{self})
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68 appoggio=[]; %
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69 appoggio=zeros(1,ns(self)); %
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70 r = evidence{self}; %...if self is observed => in output there's only the probability of the 'true' class
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71 for i=1:dpsize %
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72 appoggio(i)=T(i,r); %
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73 end
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74 T=zeros(dpsize,1);
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75 for i=1:dpsize
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76 T(i,1)=appoggio(i);
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77 end
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78 clear appoggio;
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79 ns(self) = 1;
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80 end
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