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Diffstat (limited to 'sourcecodes/parameter_learning/parameterLearning.m')
| -rw-r--r-- | sourcecodes/parameter_learning/parameterLearning.m | 5 |
1 files changed, 3 insertions, 2 deletions
diff --git a/sourcecodes/parameter_learning/parameterLearning.m b/sourcecodes/parameter_learning/parameterLearning.m index 3ef6c0b3..2c4a1f9f 100644 --- a/sourcecodes/parameter_learning/parameterLearning.m +++ b/sourcecodes/parameter_learning/parameterLearning.m @@ -4,7 +4,7 @@ function [ bnet ] = parameterLearning( bnet,cases,engine_name ) % % This is very basic now. It could be modified to use different engine % types in the future. Now, I always use the 'jtree_inf_engine'. -% +% with dirichlet priors % % parameterLearning is called by runBN_initial.m, % Predictmultiple.m, and Predictmultipleintervention.m @@ -35,7 +35,8 @@ nnodes = size(dnodes,2)+size(cnodes,2); %make dnodes tabular_CPT for i = 1:size(dnodes,2) - bnet.CPD{dnodes(i)} = tabular_CPD(bnet,dnodes(i)); +% bnet.CPD{dnodes(i)} = tabular_CPD(bnet,dnodes(i)); + bnet.CPD{dnodes(i)} = tabular_CPD(bnet,dnodes(i),'prior_type','dirichlet'); end for i = 1:size(cnodes,2) |