Defining Classes of Influences for the Acquisition of Probability Constraints for Bayesian Networks
نویسندگان
چکیده
The task of eliciting all probabilities required for a Bayesian network can be supported by first acquiring qualitative constraints on the numerical quantities to be obtained. Building upon the concept of qualitative influence, we analyse such constraints and define a small number of influence classes. Based upon these classes, we present a method for efficiently acquiring the qualitative constraints that should be satisfied by the network’s probabilities.
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