fairadapt: Fair Data Adaptation with Quantile Preservation

An implementation of the fair data adaptation with quantile preservation described in Plecko & Meinshausen (2019) <arXiv:1911.06685>. The adaptation procedure uses the specified causal graph to pre-process the given training and testing data in such a way to remove the bias caused by the protected attribute. The procedure uses tree ensembles for quantile regression.

Version: 0.2.0
Depends: R (≥ 3.5.0)
Imports: ranger (≥ 0.13.1), assertthat, quantreg, qrnn, igraph, ggplot2, cowplot, scales
Suggests: testthat (≥ 2.1.0), knitr, rmarkdown, markdown, data.table, rticles, mvtnorm
Published: 2021-07-28
Author: Drago Plecko [aut, cre]
Maintainer: Drago Plecko <drago.plecko at stat.math.ethz.ch>
BugReports: https://github.com/dplecko/fairadapt/issues
License: GPL (≥ 3)
URL: https://github.com/dplecko/fairadapt
NeedsCompilation: no
Language: en-US
Materials: README NEWS
CRAN checks: fairadapt results

Downloads:

Reference manual: fairadapt.pdf
Vignettes: Fair Data Adaptation (Plecko, JSS 2020)
Package source: fairadapt_0.2.0.tar.gz
Windows binaries: r-devel: fairadapt_0.2.0.zip, r-release: fairadapt_0.2.0.zip, r-oldrel: fairadapt_0.2.0.zip
macOS binaries: r-release (arm64): fairadapt_0.2.0.tgz, r-release (x86_64): fairadapt_0.2.0.tgz, r-oldrel: fairadapt_0.2.0.tgz
Old sources: fairadapt archive

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