ArticleJournal of the Royal Society, Interface2013
Towards a simplification of models using regression trees.
Article in Journal of the Royal Society, Interface, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Impact of Thermoelectric Power Plant Operations and Water Use Reporting Methods on Thermoelectric Power Plant Water Use.Environmental science & technology · 2025Article
- Predicting sea levels using ML algorithms in selected locations along coastal Malaysia.Heliyon · 2023Article
- Modelling the linkage between coral assemblage structure and pattern of environmental forcing.Royal Society open science · 2020Article
- Herbivore space use influences coral reef recovery.Royal Society open science · 2016Article
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Authors and funding
4 authors.
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Abstract
Over-parametrization in modelling is a well-known issue that makes it hard to identify which part of a model is responsible for a given behaviour. In line with that ascertainment, this work presents the outline of an empirical method to simplify models by decreasing the number of parameters. By using regression trees to classify outputs according to related input parameters, the method provides the modeller with an objective tool to reduce the range of the used parameters and, under certain conditions, to establish relations between them. Thereby, the complexity of the model is reduced on the basis of mathematical arguments. As an example, a dynamic energy budget-based model of a mesopelagic bacterial ecosystem is simplified using the presented method. The main benefits of such a method are thus highlighted: (i) more robust parameter estimations; (ii) less complex formulations; and (iii) fewer modelling assumptions. To conclude, the difficulties encountered are discussed, and several solutions are proposed to deal with them.
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