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forestError: A Unified Framework for Random Forest Prediction Error Estimation

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.

Version: 1.1.0
Imports: data.table, purrr
Suggests: randomForest
Published: 2021-08-10
DOI: 10.32614/CRAN.package.forestError
Author: Benjamin Lu and Johanna Hardin
Maintainer: Benjamin Lu <b.lu at berkeley.edu>
License: GPL-3
NeedsCompilation: no
Citation: forestError citation info
Materials: README NEWS
CRAN checks: forestError results

Documentation:

Reference manual: forestError.pdf

Downloads:

Package source: forestError_1.1.0.tar.gz
Windows binaries: r-devel: forestError_1.1.0.zip, r-release: forestError_1.1.0.zip, r-oldrel: forestError_1.1.0.zip
macOS binaries: r-release (arm64): forestError_1.1.0.tgz, r-oldrel (arm64): forestError_1.1.0.tgz, r-release (x86_64): forestError_1.1.0.tgz, r-oldrel (x86_64): forestError_1.1.0.tgz
Old sources: forestError archive

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.