Exploiting Experts' Knowledge for Structure Learning of Bayesian Networks.

@article{Amirkhani2016ExploitingEK,
  title={Exploiting Experts' Knowledge for Structure Learning of Bayesian Networks.},
  author={Hossein Amirkhani and Mohammad Rahmati and Peter Lucas and Arjen Hommersom},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  year={2016}
}
Learning Bayesian network structures from data is known to be hard, mainly because the number of candidate graphs is super-exponential in the number of variables. Furthermore, using observational data alone, the true causal graph is not discernible from other graphs that model the same set of conditional independencies. In this paper, it is investigated whether Bayesian network structure learning can be improved by exploiting the opinions of multiple domain experts regarding cause-effect… CONTINUE READING
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