Distributional Random Forests

Documentation for package ‘drf’ version 1.1.0

drf	Distributional Random Forests
get_sample_weights	Given a trained forest and test data, compute the training sample weights for each test point.
get_tree	Retrieve a single tree from a trained forest object.
leaf_stats.default	A default leaf_stats for forests classes without a leaf_stats method that always returns NULL.
leaf_stats.drf	Calculate summary stats given a set of samples for regression forests.
medianHeuristic	Compute the median heuristic for the MMD bandwidth choice
plot.drf_tree	Plot a DRF tree object.
predict.drf	Predict with a drf forest
print.drf	Print a DRF forest object.
print.drf_tree	Print a DRF tree object.
split_frequencies	Calculate which features the forest split on at each depth.
variableImportance	Variable importance based on MMD
variable_importance	Calculate a simple measure of 'importance' for each feature.
weighted.quantile	Weighted quantiles