Evaluation of six methods for correcting bias in estimates from ensemble tree machine learning regression models

Author:

Belitz K.,Stackelberg P.E.ORCID

Funder

U.S. Geological Survey

Publisher

Elsevier BV

Subject

Ecological Modeling,Environmental Engineering,Software

Reference45 articles.

1. Multiorder hydrologic position in the conterminous United States: a set of metrics in support of groundwater mapping at regional and national scales;Belitz;Water Resour. Res.,2019

2. Data Release for Evaluation of Six Methods for Correcting Bias in Estimates from Ensemble Tree Machine Learning Regression Models;Belitz;U.S. Geological Survey Data Release,2021

3. Object-based correction of LiDAR DEMs using RTK-GPS data and machine learning modeling in the coastal Everglades;Cooper;Environ. Model. Software,2019

4. Machine-learning models to map pH and redox conditions in groundwater in a layered aquifer system, Northern Atlantic Coastal Plain, eastern USA;DeSimone;J. Hydrol.: Reg. Stud.,2020

5. Smearing estimate – a nonparametric retransformation method;Duan;J. Am. Stat. Assoc.,1983

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