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Newer classification and regression tree techniques: Bagging and Random Forests for ecological predictionAuthor(s): Anantha M. Prasad; Louis R. Iverson; Andy Liaw; Andy Liaw
Source: Ecosystems. (9): 181-199.
Publication Series: Miscellaneous Publication
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DescriptionWe evaluated four statistical models - Regression Tree Analysis (RTA), Bagging Trees (BT), Random Forests (RF), and Multivariate Adaptive Regression Splines (MARS) - for predictive vegetation mapping under current and future climate scenarios according to the Canadian Climate Centre global circulation model.
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CitationPrasad, Anantha M.; Iverson, Louis R.; Liaw, Andy. 2006. Newer classification and regression tree techniques: Bagging and Random Forests for ecological prediction. Ecosystems. (9): 181-199.
Keywordspredictive mapping, data mining, classification and regression trees (CART), Regression Tree Analysis (RTA), decision tree, Multivariate Adaptive Regression Splines (MARS), Bagging Trees, Random Forests, Kappa, fuzzy Kappa, Canadian Climate Centre (CCC), global circulation model (GCM), eastern United State
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