Package: fairadapt 0.2.6
Drago Plecko
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.
Authors:
fairadapt_0.2.6.tar.gz
fairadapt_0.2.6.zip(r-4.7)fairadapt_0.2.6.zip(r-4.6)fairadapt_0.2.6.zip(r-4.5)
fairadapt_0.2.6.tgz(r-4.6-any)fairadapt_0.2.6.tgz(r-4.5-any)
fairadapt_0.2.6.tar.gz(r-4.7-any)fairadapt_0.2.6.tar.gz(r-4.6-any)
fairadapt_0.2.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
fairadapt/json (API)
NEWS
| # 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:2171b98f7b. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 168 | ||
| source / vignettes | OK | 215 | ||
| linux-release-x86_64 | OK | 176 | ||
| macos-release-arm64 | OK | 210 | ||
| macos-oldrel-arm64 | OK | 238 | ||
| windows-devel | OK | 123 | ||
| windows-release | OK | 116 | ||
| windows-oldrel | OK | 109 | ||
| wasm-release | OK | 154 |
Exports:adaptedDatacomputeQuantsfairadaptfairadaptBootfairTwinsgraphModellinearQuantsmcqrnnQuantsquantFitrangerQuantsvisualizeGraph
Dependencies:assertthatclicowplotcpp11farverggplot2gluegtableigraphisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelspkgconfigqrnnquantregR6rangerRColorBrewerRcppRcppEigenrlangS7scalesSparseMsurvivalvctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Convenience function for returning adapted data | adaptedData adaptedData.fairadapt adaptedData.fairadaptBoot |
| COMPAS dataset. | compas |
| Compute Quantiles generic for the Quantile Learning step. | computeQuants |
| Fairadapt | fairadapt |
| Fairadapt Boostrap wrapper | fairadaptBoot |
| Fair Twin Inspection convenience function. | fairTwins |
| Census information of US government employees. | gov_census |
| Obtaining the graphical causal model (GCM) | graphModel |
| Prediction function for new data from a saved 'fairadapt' object. | predict.fairadapt |
| Prediction function for new data from a saved 'fairadaptBoot' object. | predict.fairadaptBoot |
| Quality of quantile fit statistics. | quantFit |
| Quantile Engine Constructor for the Quantile Learning step. | linearQuants mcqrnnQuants rangerQuants |
| University admission data of 1,000 students. | uni_admission |
| Visualize Graphical Causal Model | visualizeGraph |