diff options
| author | ziejd2 | 2018-03-14 23:19:16 -0500 |
|---|---|---|
| committer | ziejd2 | 2018-03-14 23:19:16 -0500 |
| commit | c80226899f5cdd9f11c163817d59445213f5bef0 (patch) | |
| tree | e0fd79d2e32fd2aedda2eadaed0f19af3514c520 /sourcecodes/parameter_learning/runBN_initial.m | |
| parent | 324ebc8ddacab8e154047b8518afd5cbb5bb2fa4 (diff) | |
| download | BNW-c80226899f5cdd9f11c163817d59445213f5bef0.tar.gz | |
Separating Octave and php calculations
Diffstat (limited to 'sourcecodes/parameter_learning/runBN_initial.m')
| -rw-r--r-- | sourcecodes/parameter_learning/runBN_initial.m | 87 |
1 files changed, 23 insertions, 64 deletions
diff --git a/sourcecodes/parameter_learning/runBN_initial.m b/sourcecodes/parameter_learning/runBN_initial.m index 789b4260..c2dec164 100644 --- a/sourcecodes/parameter_learning/runBN_initial.m +++ b/sourcecodes/parameter_learning/runBN_initial.m @@ -15,84 +15,43 @@ mapfile = fopen(mapfilename,'w'); mapval = fopen(mapvalfilename,'w'); -%nnodes=5; Std_flag=true; [labels,cases,bnet,node_sizes,data,labelsold]=readInput(dfile,sfile,nnodes,Std_flag); -s = std(data,0,1); +s=std(data,0,1); m=mean(data); - for i=1:nnodes fprintf(mapval,'%s\t%d\t%f\t%f\n',labelsold{i},node_sizes(i),s(i),m(i)); end - -% for j=1:nnodes -% [next,buffer] = strtok(buffer); -% name{j}=next; -% for i=1:nnodes -% if strcmp(name{j},labels{i}) -% map{j}=i; -% fprintf(mapfile,'%d\t',i); -% end -% end -% end -%name -%labels -%map fprintf(mapfile,'%s',labels{1}); for i=2:nnodes fprintf(mapfile,'\t%s',labels{i}); end fprintf(mapfile,'\n'); +fclose(mapval); +fclose(mapfile); + +%Need to rearrange the means and stdevs to match the new labeling. +means = cell(1,nnodes); +stdevs = cell(1,nnodes); +for i = 1:nnodes + for j = 1:nnodes + if strcmp(labels{i},labelsold{j}) + means{i} = m(j); + stdevs{i} = s(j); + break + end + end +end + [bnet]=parameterLearning(bnet,cases); -%[predict_mean,predict_sd,q_sq]=looCrossValid(bnet,cases); -%engine=jtree_inf_engine(bnet); -%evidence=cell(1,nnodes); - -%varfile='var.txt'; -%fvar = fopen(varfile,'r'); -%select_var = fscanf(fvar,'%d'); -%select_var=map{select_var}; -%varfiled='vardata.txt'; -%fvard = fopen(varfiled,'r'); -%select_var_data = fscanf(fvard,'%f'); - -%evidence{select_var}=select_var_data; -%[engine,loglik]=enter_evidence(engine,evidence); - -%outdata='prediction.txt'; -%fout = fopen(outdata,'w'); - -%for ii = 1:nnodes - % i=map{ii}; - % data=marginal_nodes(engine,i); - % fprintf(fout,'%d\t%d\t%f\t%f\t%f\n',ii,data.domain,data.T,data.mu,data.Sigma); - %fprintf(1,'%d\n',i); -% end filename=strcat(pre,'net_figure.txt'); -drawFigure(nnodes,bnet,labels,filename,cases); - -%quit force; -%marginal_nodes(engine,2) -%marginal_nodes(engine,3) -%marginal_nodes(engine,4) -%marginal_nodes(engine,5) -%evidence{1}=2; -%[engine,loglik]=enter_evidence(engine,evidence) -%marginal_nodes(engine,1) -%marginal_nodes(engine,2) -%marginal_nodes(engine,3) -%marginal_nodes(engine,4) -%marginal_nodes(engine,5) -%evidence{2}=0.6; -%evidence{1}=[]; -%[engine,loglik]=enter_evidence(engine,evidence); -%marginal_nodes(engine,3); -%marginal_nodes(engine,4); -%marginal_nodes(engine,5); -fclose(mapval); -fclose(mapfile); -end \ No newline at end of file + +drawFigure(nnodes,bnet,labels,filename,cases,stdevs,means); + +writeParameters(pre,nnodes,bnet,labels,cases,labelsold,s,m); + +end |
