forestError: A Unified Framework for Random Forest Prediction Error
Estimates the conditional error distributions of random forest
predictions and common parameters of those distributions, including
conditional misclassification rates, conditional mean squared prediction
errors, conditional biases, and conditional quantiles, by out-of-bag
weighting of out-of-bag prediction errors as proposed by Lu and Hardin
(2021). This package is compatible with several existing packages that
implement random forests in R.
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