Variable Importance in Random Forests

Traditional Methods and New Developments

Random Forest and generalizations (in particular, Generalized Random Forests (GRF) and Distributional Random Forests (DRF) ) are powerful and easy-to-use machine learning methods that should not be absent in the toolbox of any data scientist. They not only show robust performance over a large range of datasets without the need for tuning, but can also easily handle missing values …

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