Explaining inferences in Bayesian networks

  title={Explaining inferences in Bayesian networks},
  author={Ghim-Eng Yap and Ah-Hwee Tan and HweeHwa Pang},
  journal={Applied Intelligence},
While Bayesian network (BN) can achieve accurate predictions even with erroneous or incomplete evidence, explaining the inferences remains a challenge. Existing approaches fall short because they do not exploit variable interactions and cannot account for compensations during inferences. This paper proposes the Explaining BN Inferences (EBI) procedure for explaining how variables interact to reach conclusions. EBI explains the value of a target node in terms of the influential nodes in the… CONTINUE READING
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