Consider a simple Bayesian network with root variables ${Cold}$,
${Flu}$, and ${Malaria}$ and child variable ${Fever}$, with a
noisy-OR conditional distribution for ${Fever}$ as described in
Section canonical-distribution-section. By adding
appropriate auxiliary variables for inhibition events and fever-inducing
events, construct an equivalent Bayesian network whose CPTs (except for
root variables) are deterministic. Define the CPTs and prove
equivalence.
Consider a simple Bayesian network with root variables ${Cold}$, ${Flu}$, and ${Malaria}$ and child variable ${Fever}$, with a noisy-OR conditional distribution for ${Fever}$ as described in Section canonical-distribution-section. By adding appropriate auxiliary variables for inhibition events and fever-inducing events, construct an equivalent Bayesian network whose CPTs (except for root variables) are deterministic. Define the CPTs and prove equivalence.