Discretization of continuous predictor variables in Bayesian networks: an ecological threshold approach
Article
Article Title | Discretization of continuous predictor variables in Bayesian networks: an ecological threshold approach |
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ERA Journal ID | 4673 |
Article Category | Article |
Authors | Lucena-Moya, Paloma (Author), Brawata, Renee (Author), Kath, Jarrod (Author), Harrison, Evan (Author), El Sawah, Sondoss (Author) and Dyer, Fiona (Author) |
Journal Title | Environmental Modelling and Software |
Journal Citation | 66, pp. 36-45 |
Number of Pages | 10 |
Year | 2015 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 1364-8152 |
1873-6726 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.envsoft.2014.12.019 |
Abstract | 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 |
Keywords | Bayesian networks, thresholds, aquatic ecology, macroinvertebrates, ecological community, TITAN, discretization |
ANZSRC Field of Research 2020 | 410404. Environmental management |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Institution of Origin | University of Southern Queensland |
Byline Affiliations | University of Canberra |
Australian National University |
https://research.usq.edu.au/item/q4xqz/discretization-of-continuous-predictor-variables-in-bayesian-networks-an-ecological-threshold-approach
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