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| ## `aif360.sklearn` | |
| This is a wholly separate interface for interacting with data, viewing metrics, | |
| and running debiasing algorithms than the main AIF360 package. The purpose of | |
| this sub-package is to match scikit-learn paradigms/APIs for easier integration | |
| in typical machine learning workflows. | |
| See [Getting Started](examples/Getting%20Started.ipynb) to see `aif360.sklearn` | |
| in action. | |
| To do: | |
| - [x] Reformat datasets as separate X and y (and sample_weight) DataFrame | |
| objects with sample properties (protected attributes) as the index | |
| - [ ] Load included datasets in the above format | |
| - [x] Use `sklearn.datasets.fetch_openml` to load UCI datasets (#53) | |
| - [ ] COMPAS | |
| - [ ] MEPS | |
| - [ ] Implement metrics as individual functions instead of instance methods | |
| - [x] Make certain metrics compatible as sklearn scorers | |
| - [x] Use "prot_attr" and "priv_group" keywords to specify protected attributes to | |
| functions | |
| - [x] Generalized confusion matrix | |
| - [ ] Sample distortion metrics | |
| - [ ] Make inprocessing algorithms compatible as sklearn `Estimator`s | |
| - [x] Adversarial debiasing | |
| - [ ] **[External]** `get_feature_names()` from data preprocessing | |
| steps that would remove DataFrame formatting | |
| - [ ] [SLEP007](https://github.com/scikit-learn/enhancement_proposals/pull/17)/[SLEP008](https://github.com/scikit-learn/enhancement_proposals/pull/18) - feature names | |
| - [ ] Prejudice remover | |
| - [ ] Meta-fair classifier | |
| - [ ] Make preprocessing algorithms compatible as sklearn `Transformer`s | |
| - [ ] **[External]** Add functionality to modify X and y | |
| - [ ] [SLEP005](https://github.com/scikit-learn/enhancement_proposals/pull/15) - Resampler API (see discussion; meta-estimator workaround may be enough) | |
| - [ ] Disparate impact remover | |
| - [ ] Learning fair representations | |
| - [ ] Optimized preprocessing | |
| - [X] Reweighing | |
| - [X] Meta-estimator workaround | |
| - [ ] **[External]** [SLEP006](https://github.com/scikit-learn/enhancement_proposals/pull/16) - Sample properties (meta-estimator works but would be very nice to have) | |
| - [ ] Make postprocessing algorithms compatible | |
| - [x] Calibrated equalized odds postprocessing | |
| - [x] Meta-estimator workaround again | |
| - [ ] Equalized odds postprocessing | |
| - [ ] Reject option classification | |
| - [ ] Miscellaneous: | |
| - [ ] Explainers | |