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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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Bibliographische Detailangaben
Veröffentlicht in:Environ Monit Assess
Hauptverfasser: Fox, Eric W., Hill, Ryan A., Leibowitz, Scott G., Olsen, Anthony R., Thornbrugh, Darren J., Weber, Marc H.
Format: Artigo
Sprache:Inglês
Veröffentlicht: 2017
Schlagworte:
Online Zugang: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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