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Erschienen in:
2013 | OriginalPaper | Buchkapitel
6. Eliciting the Model
verfasst von : Uffe B. Kjærulff, Anders L. Madsen
Erschienen in: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
Verlag: Springer New York
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Abstract
A probabilistic network consists of two components: structure and parameters [i.e., conditional probabilities and utilities (statements of preference)]. The structure of a probabilistic network is often referred to as the qualitative part of the network, whereas the parameters are often referred to as its quantitative part. As the parameters of a model are determined by its structure, the model elicitation process always proceeds in two consecutive stages: First, the variables and the causal, functional or informational relations among the variables are identified, providing the qualitative part of the model. Second, once the model structure has been determined through an iterative process involving testing of variables and conditional independences, and verification of the directionality of the links, the values of the parameters are elicited.