Abstract
Most documented Bayesian network (BN) applications have been built through knowledge elicitation from domain experts (DEs), The difficulties involved have led to growing interest in machine learning of BNs from data. There is a further need for combining what can be learned from the data with what can be elicited from DEs. In this paper, we propose a detailed methodology for this combination, specifically for the parameters of a BN. © Springer-Verlag Berlin Heidelberg 2004.
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CITATION STYLE
Woodberry, O., Nicholson, A. E., Korb, K. B., & Pollino, C. (2004). Parameterising Bayesian networks. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3339, pp. 1101–1107). Springer Verlag. https://doi.org/10.1007/978-3-540-30549-1_108
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