Package: fairadapt 1.0.0
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>.
Authors:
fairadapt_1.0.0.tar.gz
fairadapt_1.0.0.zip(r-4.7-any)fairadapt_1.0.0.zip(r-4.6-any)fairadapt_1.0.0.zip(r-4.5-any)
fairadapt_1.0.0.tgz(r-4.6-any)fairadapt_1.0.0.tgz(r-4.5-any)
fairadapt_1.0.0.tar.gz(r-4.7-any)fairadapt_1.0.0.tar.gz(r-4.6-any)
fairadapt_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
fairadapt/json (API)
| # Install 'fairadapt' in R: |
| install.packages('fairadapt', repos = c('https://dplecko.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dplecko/fairadapt/issues
- compas - COMPAS dataset
- gov_census - Census information of US government employees
- uni_admission - University admission data of 1,000 students
causal-inferencefairnessmachine-learning
Last updated from:d766469f1b. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 150 | ||
| source / vignettes | OK | 212 | ||
| linux-release | OK | 158 | ||
| macos-release | OK | 158 | ||
| macos-oldrel | OK | 144 | ||
| windows-devel | OK | 120 | ||
| windows-release | OK | 108 | ||
| windows-oldrel | OK | 127 | ||
| wasm-release | OK | 122 |
Exports:adaptedDatacomputeQuantsfairadaptfairadaptBootfairTwinsgraphModellinearQuantsmcqrnnQuantsquantFitrangerQuantsvisualizeGraph
Dependencies:assertthatclicowplotcpp11farverggplot2gluegtableigraphisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelspkgconfigqrnnquantregR6rangerRColorBrewerRcppRcppEigenrlangS7scalesSparseMsurvivalvctrsviridisLitewithr