文摘
An experiment was designed to evaluate the impact of commonly used discretization methods and number of intervals on the developed Bayesian Networks (BNs). The conditional probability tables, and hence, model predictions and management recommendations differed among models. None of the models did uniformly well in all comparison criteria. It is suggested that discretization be used with caution or be avoided, when possible, and the BN models be modified to accommodate continuous variables. A verification process is recommended that includes evaluating alternative methods to ensure that the conclusions are not an artifact of the discretization approach.