MIT doctoral developed extremely powerful Bayesian Network Toolbox (MATLAB environment) to support a variety of parameter learning and structure learning algorithm, containing a detailed description of

FullBNT-1.0.4
.............\#ChangeLog.txt#
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.............\...\....\..................\deterministic_CPD.m
.............\...\....\@discrete_CPD
.............\...\....\.............\convert_CPD_to_table_hidden_ps.m
.............\...\....\.............\convert_obs_CPD_to_table.m
.............\...\....\.............\convert_to_pot.m
.............\...\....\.............\convert_to_sparse_table.c
.............\...\....\.............\convert_to_table.m
.............\...\....\.............\CPD_to_lambda_msg.m
.............\...\....\.............\CPD_to_pi.m
.............\...\....\.............\CPD_to_scgpot.m
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.............\...\....\.............\log_prob_node.m
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.............\...\....\.............\...\convert_to_table.m
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.............\...\....\.............\README
.............\...\....\.............\sample_node.m
.............\...\....\@gaussian_CPD
.............\...\....\.............\adjustable_CPD.m
.............\...\....\.............\convert_CPD_to_table_hidden_ps.m
.............\...\....\.............\convert_to_pot.m
.............\...\....\.............\convert_to_table.m
.............\...\....\.............\CPD_to_lambda_msg.m
.............\...\....\.............\CPD_to_pi.m
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.............\...\....\.............\gaussian_CPD.m
.............\...\....\.............\gaussian_CPD_params_given_dps.m
.............\...\....\.............\get_field.m
.............\...\....\.............\learn_params.m
.............\...\....\.............\log_prob_node.m
.............\...\....\.............\maximize_params.m
.............\...\....\.............\maximize_params_debug.m
.............\...\....\.............\Old
.............\...\....\.............\...\CPD_to_lambda_msg.m
.............\...\....\.............\...\CVS
.............\...\....\..

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