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-4.5)fairadapt_0.2.6.zip(r-4.4)fairadapt_0.2.6.zip(r-4.3)
fairadapt_0.2.6.tgz(r-4.4-any)fairadapt_0.2.6.tgz(r-4.3-any)
fairadapt_0.2.6.tar.gz(r-4.5-noble)fairadapt_0.2.6.tar.gz(r-4.4-noble)
fairadapt_0.2.6.tgz(r-4.4-emscripten)fairadapt_0.2.6.tgz(r-4.3-emscripten)
fairadapt.pdf |fairadapt.html✨
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 1 years agofrom:2171b98f7b. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 10 2024 |
| R-4.5-win | OK | Nov 10 2024 |
| R-4.5-linux | OK | Nov 10 2024 |
| R-4.4-win | OK | Nov 10 2024 |
| R-4.4-mac | OK | Nov 10 2024 |
| R-4.3-win | OK | Nov 10 2024 |
| R-4.3-mac | OK | Nov 10 2024 |
Exports:adaptedDatacomputeQuantsfairadaptfairadaptBootfairTwinsgraphModellinearQuantsmcqrnnQuantsquantFitrangerQuantsvisualizeGraph
Dependencies:assertthatclicolorspacecowplotcpp11fansifarverggplot2gluegtableigraphisobandlabelinglatticelifecyclemagrittrMASSMatrixMatrixModelsmgcvmunsellnlmepillarpkgconfigqrnnquantregR6rangerRColorBrewerRcppRcppEigenrlangscalesSparseMsurvivaltibbleutf8vctrsviridisLitewithr
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 |