comparison toolboxes/FullBNT-1.0.7/bnt/learning/learn_params.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function bnet = learn_params(bnet, data)
+% LEARN_PARAMS Find the maximum likelihood params for a fully observed model
+% bnet = learn_params(bnet, data)
+%
+% data(i,m) is the value of node i in case m (can be a cell array)
+%
+% We set bnet.CPD{i} to its ML/MAP estimate.
+%
+% Currently we assume no param tying
+
+% AND THAT EACH DATA POINT IS A SCALAR - no longer assumed
+
+%if iscell(data)
+%  data=cell2num(data);
+%end
+[n ncases] = size(data);
+for j=1:n
+  e = bnet.equiv_class(j);
+  assert(e==j);
+  if adjustable_CPD(bnet.CPD{e})
+    fam = family(bnet.dag,j);
+    %bnet.CPD{j} = learn_params(bnet.CPD{j}, data(fam,:));
+    bnet.CPD{j} = learn_params(bnet.CPD{j}, fam, data, bnet.node_sizes, bnet.cnodes);
+  end
+end
+