Discretization of continuous predictor variables in Bayesian networks: an ecological threshold approach
Bayesian networks (BNs) are a popular tool in natural resource management but are limited when dealing with ecological assemblage data and when discretizing continuous variables. We present a method that addresses these challenges using a BN model developed for the Upper Murrumbidgee River Catchment (south-eastern Australia). A selection process was conducted to choose the taxa from the whole macroinvertebrate assemblage that were incorporated in the BN as endpoints. Furthermore, two different...[Show more]
|Collections||ANU Research Publications|
|Source:||Environmental Modelling & Software|
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