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Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology

Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected s...

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Detalhes bibliográficos
Publicado no:Environ Monit Assess
Main Authors: Fox, Eric W., Hill, Ryan A., Leibowitz, Scott G., Olsen, Anthony R., Thornbrugh, Darren J., Weber, Marc H.
Formato: Artigo
Idioma:Inglês
Publicado em: 2017
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6049094/
https://ncbi.nlm.nih.gov/pubmed/28589457
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s10661-017-6025-0
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