fairadapt: Fair Data Adaptation with Quantile Preservation
An implementation of the fair data adaptation with quantile
preservation described in Plecko & Meinshausen (JMLR 2020, 21(242), 1-44).
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. Instructions for using the methods are further elaborated in
the corresponding JSS manuscript, see <doi:10.18637/jss.v110.i04>.
| Version: |
1.0.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
ranger (≥ 0.13.1), assertthat, quantreg, qrnn, igraph, ggplot2, cowplot, scales |
| Suggests: |
testthat (≥ 3.0.3), knitr, rmarkdown, rticles, mvtnorm, magick, ggraph, pdftools, microbenchmark, xtable, spelling |
| Published: |
2024-09-06 |
| DOI: |
10.32614/CRAN.package.fairadapt |
| Author: |
Drago Plecko [aut, cre],
Nicolas Bennett [aut] |
| Maintainer: |
Drago Plecko <www.plecko at gmail.com> |
| BugReports: |
https://github.com/dplecko/fairadapt/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://github.com/dplecko/fairadapt |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Citation: |
fairadapt citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
fairadapt results |
Documentation:
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