Prediction using a BN is straightforward and can generally proceed most effectively using Monte Carlo simulation. The findings for a node are represented by a marginal (discrete or continuous) probability distribution, which is used to generate a large random sample for that variable. This sample is then used as input to the function(s) defining that node's descendant(s), along with samples from any other uncertain variables that are required by the function(s). This generates a sample of the first generation of descendents, which is propagated further along the causal direction in an analogous manner until the query node is reached. The sample for the query node can then be used to estimate the statistics or full distribution for the corresponding variable.
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