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	1	Stream water quality prediction using boosted regression tree and random forest models Enthalten in Stochastic environmental research and risk assessment 20.1.2022: 1-20
	2	Comparison of gradient boosted decision trees and random forest for groundwater potential mapping in Dholpur (Rajasthan), India Enthalten in Stochastic environmental research and risk assessment 6.10.2020: 1-20
	3	Boosted Random Forest Müntefering, Eva-Maria, 2016
	4	Erratum to: Landslide susceptibility mapping using random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their performance at Wadi Tayyah Basin, Asir Region, Saudi Arabia In: Landslides 30.12.2015: 1-4
	5	A comparative study of land subsidence susceptibility mapping of Tasuj plane, Iran, using boosted regression tree, random forest and classification and regression tree methods Enthalten in Environmental earth sciences Bd. 79, 12.5.2020, Nr. 10, date:5.2020: 1-12
	6	GIS-based groundwater potential mapping using boosted regression tree, classification and regression tree, and random forest machine learning models in Iran In: Environmental monitoring and assessment Bd. 188, 19.12.2015, Nr. 1, date:1.2016: 1-27
	7	Landslide susceptibility mapping using random forest, boosted regression tree, classification and regression tree, and general linear models and comparison of their performance at Wadi Tayyah Basin, Asir Region, Saudi Arabia In: Landslides Bd. 13, 8.8.2015, Nr. 5, date:10.2016: 839-856

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