Cannot see the random forest for the decision trees: selecting predictive models for restoration ecology

Improving predictions of restoration outcomes is increasingly important to resource managers for accountability and adaptive management, yet there is limited guidance for selecting a predictive model from the multitude available. The goal of this article was to identify an optimal predictive framewo...

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Veröffentlicht in:Restoration ecology Jg. 27; H. 5; S. 1053 - 1063
Hauptverfasser: Barnard, David M., Germino, Matthew J., Pilliod, David S., Arkle, Robert S., Applestein, Cara, Davidson, Bill E., Fisk, Matthew R.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Malden, USA Wiley Periodicals, Inc 01.09.2019
Blackwell Publishing Ltd
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ISSN:1061-2971, 1526-100X
Online-Zugang:Volltext
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