Bayesian Networks: the Range of the Prior Convergence Error
نویسنده
چکیده
In a Bayesian network, a convergence error may arise in the probabilities computed for a node with two or more parents in the same loop (in this paper such a node is called a convergence node), when in the computation of these probabilities the information of the parents is processed as if they are independent. In this paper the range of the convergence error for the basic case of a loop with just one convergence node given a binary network in its prior state is investigated. It is found that, given two parents in the loop, the range of the prior convergence error changes from [−0.5, 0] given a prior probability of the child node of 0, to [0, 0.5] given a prior probability of the child node of 1. The ranges of the prior convergence error extend to 〈−1, 0] and [0, 1〉 when the number of parents grows to infinity.
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