Monash University
tr-2004-159-full.pdf (640.73 kB)
Download file

Parameterising Bayesian Networks: A Case Study in Ecological Risk Assessment

Download (640.73 kB)
posted on 2022-08-29, 04:56 authored by O Woodberry, A Nicholson, K Korb, C Pollino
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 front DEs. In this paper, we propose a detailed methodology for this combination, specifically for the parameters of a BN. We illustrate the techniques using a case study of an ecological risk assessment (ERA) problem, specifically the Goulburn Catchment (Victoria, Australia) ERA project.


Technical report number


Year of publication


Usage metrics

    Monash Information Technology Technical Reports