Aif360

Latest version: v0.6.0

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0.6.0

Highlights
* New algorithms:
* `SenSeI`/`SenSR`
* `DeterministicReranking`
* New metric:
* `ot_distance`

Backwards-Incompatible Changes
* Dropped support for `bias_scan` from `aif360.metrics`/`aif360.sklearn.metrics`
* Minor changes to MEPS files

What's Changed
* Add python 3.10 for testing in ci.yml by hakimamarullah in https://github.com/Trusted-AI/AIF360/pull/368
* Allow binder to automatically build environment by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/395
* Update to demo_lime notebook to run out of the box (and in Google collab) by anupamamurthi in https://github.com/Trusted-AI/AIF360/pull/396
* Fix error in metric_json_explainer.consistency() by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/400
* Solving issue 381, to run demo_new_features notebook in Colab by ivesulca in https://github.com/Trusted-AI/AIF360/pull/402
* logic error in disparate_impact and statistical_parity_difference 292 by sreeja-g in https://github.com/Trusted-AI/AIF360/pull/407
* Modify example notebooks to work in Google colab 378 by Yashaswini-Viswanath in https://github.com/Trusted-AI/AIF360/pull/405
* Solving second part of issue 381 by ivesulca in https://github.com/Trusted-AI/AIF360/pull/409
* Get notebooks in examples/sklearn/ to work in Google colab (Part 2/3) [380] by dharmod in https://github.com/Trusted-AI/AIF360/pull/403
* average predictive value difference metric implementation 376 by sreeja-g in https://github.com/Trusted-AI/AIF360/pull/410
* Add code coverage checks with `pytest-cov` by aitorres in https://github.com/Trusted-AI/AIF360/pull/412
* Initial inFairness algorithms (SenSeI/SenSR) by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/340
* Remove turtle module import by gkumbhat in https://github.com/Trusted-AI/AIF360/pull/415
* Contribution Guide by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/427
* Bump versions by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/458
* Fix typo in GridSearchReduction by haas-christian in https://github.com/Trusted-AI/AIF360/pull/452
* Add a bias detector based on optimal transport by jmarecek in https://github.com/Trusted-AI/AIF360/pull/434
* Issue 265 privileged class bank dataset by joosjegoedhart in https://github.com/Trusted-AI/AIF360/pull/449
* Fix typo. by gowriaddepalli in https://github.com/Trusted-AI/AIF360/pull/470
* Added methods for equalized odds difference by divyagaddipati in https://github.com/Trusted-AI/AIF360/pull/477
* Update data_preproc_functions.py to solve conversion to float issue by baraldian in https://github.com/Trusted-AI/AIF360/pull/498
* Add methods for dealing with fairness in rankings by andrewklayk in https://github.com/Trusted-AI/AIF360/pull/461
* Update homepage URL by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/503
* Remove deprecated bias scan metrics by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/504
* Replace deprecated `if_delegate_has_method` with `available_if` by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/511
* Fix tests failing due to int columns by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/513
* Change source for Law School GPA dataset by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/510
* Install R dependencies by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/514
* Update sphinx requirement by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/512
* Bump jinja2 from 3.0.3 to 3.1.3 by dependabot in https://github.com/Trusted-AI/AIF360/pull/507
* add .readthedocs.yaml by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/516
* Fix .readthedocs.yaml and bump version by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/517
* Fix sphinx_rtd_theme by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/518
* Rename master -> main by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/515
* Remove `requests` dependency by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/519
* Include `fairadapt.R` in package by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/520

New Contributors
* hakimamarullah made their first contribution in https://github.com/Trusted-AI/AIF360/pull/368
* anupamamurthi made their first contribution in https://github.com/Trusted-AI/AIF360/pull/396
* ivesulca made their first contribution in https://github.com/Trusted-AI/AIF360/pull/402
* sreeja-g made their first contribution in https://github.com/Trusted-AI/AIF360/pull/407
* Yashaswini-Viswanath made their first contribution in https://github.com/Trusted-AI/AIF360/pull/405
* dharmod made their first contribution in https://github.com/Trusted-AI/AIF360/pull/403
* aitorres made their first contribution in https://github.com/Trusted-AI/AIF360/pull/412
* gkumbhat made their first contribution in https://github.com/Trusted-AI/AIF360/pull/415
* haas-christian made their first contribution in https://github.com/Trusted-AI/AIF360/pull/452
* jmarecek made their first contribution in https://github.com/Trusted-AI/AIF360/pull/434
* joosjegoedhart made their first contribution in https://github.com/Trusted-AI/AIF360/pull/449
* gowriaddepalli made their first contribution in https://github.com/Trusted-AI/AIF360/pull/470
* divyagaddipati made their first contribution in https://github.com/Trusted-AI/AIF360/pull/477
* baraldian made their first contribution in https://github.com/Trusted-AI/AIF360/pull/498
* andrewklayk made their first contribution in https://github.com/Trusted-AI/AIF360/pull/461

**Full Changelog**: https://github.com/Trusted-AI/AIF360/compare/v0.5.0...v0.6.0

0.5.0

Highlights
* New algorithms:
* FairAdapt
* New metrics:
* MDSS
* `class_imbalance`, `kl_divergence`, `conditional_demographic_disparity`
* `intersection` and `one_vs_rest` meta-metrics
* sklearn-compatible ports:
* differential fairness metrics
* MEPS, COMPAS violent
* RejectOptionClassification, LearnedFairRepresentations

New Features/Improvements
* Multidimensional subset scanning (MDSS) for bias in classifiers by Viktour19 in https://github.com/Trusted-AI/AIF360/pull/238
* Update component.yaml to kfp v2 sdk by yhwang in https://github.com/Trusted-AI/AIF360/pull/259
* Fairadapt inclusion in AIF360 by dplecko in https://github.com/Trusted-AI/AIF360/pull/257
* Added a tutorial for advertising data by barvek in https://github.com/Trusted-AI/AIF360/pull/310
* More sklearn-compatible algorithms by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/318
* Dataset Improvements by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/278
* array of sample-wise protected attributes may now be passed in `prot_attr` instead of an index label
* Method of the month (July) by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/324
* sklearn-compat additions by mnagired in https://github.com/Trusted-AI/AIF360/pull/322
* add `predict_proba` to `RejectOptionClassifier`
* More sklearn-compatible metrics by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/290
* `smoothed_edf`, `df_bias_amplification`
* `class_imbalance`, `kl_divergence`, `conditional_demographic_disparity`
* `intersection`, `one_vs_rest`

Backwards-Incompatible Changes
* Add detectors api by Adebayo-Oshingbesan in https://github.com/Trusted-AI/AIF360/pull/305
* version of `bias_scan` in `aif360.metrics` to be deprecated next release

Fixes
* Fixed computation of coefficient of variation in classification_metrics by plankington in https://github.com/Trusted-AI/AIF360/pull/288
* Fix exponential gradient reduction without protected attribute (267) by jdnklau in https://github.com/Trusted-AI/AIF360/pull/268
* Remove caches due to excessive memory use by Adebayo-Oshingbesan in https://github.com/Trusted-AI/AIF360/pull/317
* fix rpy2 crash bug by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/313
* Fix pipelining bug in fairlearn algorithms by hoffmansc in https://github.com/Trusted-AI/AIF360/pull/323
* Optional tempeh, conditional imports by DanielRyszkaIBM in https://github.com/Trusted-AI/AIF360/pull/338
* Restricting AdversarialDebiasing's trainable variables to current scope by mfeffer in https://github.com/Trusted-AI/AIF360/pull/255
* Increasing max_iter to 1000 for LogisticRegression used in PrejudiceRemover by mfeffer in https://github.com/Trusted-AI/AIF360/pull/254

New Contributors
* Viktour19 made their first contribution in https://github.com/Trusted-AI/AIF360/pull/238
* jdnklau made their first contribution in https://github.com/Trusted-AI/AIF360/pull/268
* yhwang made their first contribution in https://github.com/Trusted-AI/AIF360/pull/259
* dplecko made their first contribution in https://github.com/Trusted-AI/AIF360/pull/257
* plankington made their first contribution in https://github.com/Trusted-AI/AIF360/pull/288
* Adebayo-Oshingbesan made their first contribution in https://github.com/Trusted-AI/AIF360/pull/305
* barvek made their first contribution in https://github.com/Trusted-AI/AIF360/pull/310
* milevavantuyl made their first contribution in https://github.com/Trusted-AI/AIF360/pull/309
* josue-rodriguez made their first contribution in https://github.com/Trusted-AI/AIF360/pull/315
* DanielRyszkaIBM made their first contribution in https://github.com/Trusted-AI/AIF360/pull/338
* mnagired made their first contribution in https://github.com/Trusted-AI/AIF360/pull/322
* mfeffer made their first contribution in https://github.com/Trusted-AI/AIF360/pull/255

**Full Changelog**: https://github.com/Trusted-AI/AIF360/compare/v0.4.0...v0.5.0

0.4.0

This is a major release containing a number of new features, improvements, and bugfixes.

Highlights

* TensorFlow 2, Python 3.8 now supported
* New algorithms:
* Exponentiated Gradient Reduction
* Grid Search Reduction
* New dataset:
* Law school GPA

New Features/Improvements

* Python 3.8 and TensorFlow 2 (via `compat.v1`) support added (230)
* Algorithms from fairlearn added (215):
* Exponentiated Gradient Reduction and Grid Search Reduction
* Support for regression datasets
* Law school GPA dataset added
* `MetaFairClassifier` code cleaned and sped up (196)
* removed numba dependency (187)
* `maxiter` and `maxfun` arguments in LFR `fit()` (184)

Backwards-Incompatible Changes

* Removed support for Python 3.5

Fixes

* Fix bug where `scores` in a single-row dataset was getting squeezed (193)
* Typo in `consistency_score` documentation (195)
* Lime notebook license issue (191)

New Contributors
baba-mpe, SSaishruthi, leenamurgai, synapticarbors, sohiniu, yangky11

0.3.0

This is a major release containing a number of new features, improvements, and bugfixes.

Highlights
* scikit-learn compatible API for certain algorithms, metrics, and datasets
* Documentation layout was revamped to make it easier to navigate.
* New algorithm:
* Fairness Gerrymandering [(Kearns, et al., 2018)](https://arxiv.org/abs/1711.05144)
* New metrics:
* Differential Fairness [(Foulds, et al., 2018)](https://arxiv.org/pdf/1807.08362)
* Rich Subgroup Fairness [(Kearns, et al., 2018)](https://arxiv.org/abs/1711.05144)

New Features/Improvements
* Optional dependencies may now be installed using the setuptools "extras" option: e.g., `pip install 'aif360[LFR,AdversarialDebiasing]'` or `pip install 'aif360[all]'`
* Added support for integrations with MLOps (Kubeflow and NiFi) and examples
* Added `scores` output to `AdversarialDebiasing.predict()` (139)
* Added a `subset()` method to `StructuredDataset` (140)
* Added new `MulticlassLabelDataset` to support basic multiclass problems (165)
* scikit-learn compatibility (134)
* EXPERIMENTAL: incomplete, contributions welcome
* 4 datasets (Adult, German, Bank, Compas) in DataFrame format with protected attributes in the index
* Automatically downloads from openml.org
* 6 group fairness metrics as functions (`statistical_parity_difference`, `disparate_impact_ratio`, `equal_opportunity_difference`, `average_odds_difference`, `average_odds_error`, `between_group_generalized_entropy_error`)
* 2 individual fairness metrics as functions (`generalized_entropy_index` and its variants, `consistency_score`)
* 5 additional metrics as functions (`specificity_score`, `base_rate`, `selection_rate`, `generalized_fpr`, `generalized_fnr`)
* `make_scorer` function to wrap metrics for use in sklearn cross-validation functions (174, 178)
* 3 algorithms (`Reweighing`, `AdversarialDebiasing`, `CalibratedEqualizedOdds`)

Fixes
* Fixed deprecation warning/`NotImplementedError` in `StandardDataset` (115)
* Fixed age threshold in `GermanDataset` (129 and 137)
* Corrected privileged/unprivileged attribute values for COMPAS dataset in some demos (138)
* Fixed base rate computation in EqOddsPostprocessing (170)
* Improved warning messages when missing optional packages (170)
* Multiple documentation fixes (114, 124, 153, 155, 157, 158, 159, 170)

New Contributors
autoih, romeokienzler, jimbudarz, stephanNorsten, sethneel, imolloy, guillemarsan, gdequeiroz, chajath, bhavyaghai, Tomcli, swapna-somineni, chkoar, motapaolla

0.3.0rc0

This is a major release containing a number of new features, improvements, and bugfixes.

Highlights
* scikit-learn compatible API for certain algorithms, metrics, and datasets
* Documentation layout was revamped to make it easier to navigate.
* New algorithm:
* Fairness Gerrymandering [(Kearns, et al., 2018)](https://arxiv.org/abs/1711.05144)
* New metrics:
* Differential Fairness [(Foulds, et al., 2018)](https://arxiv.org/pdf/1807.08362)
* Rich Subgroup Fairness [(Kearns, et al., 2018)](https://arxiv.org/abs/1711.05144)

New Features/Improvements
* Optional dependencies may now be installed using the setuptools "extras" option: e.g., `pip install 'aif360[LFR,AdversarialDebiasing]'` or `pip install 'aif360[all]'`
* Added support for integrations with MLOps (Kubeflow and NiFi) and examples
* Added `scores` output to `AdversarialDebiasing.predict()` (139)
* Added a `subset()` method to `StructuredDataset` (140)
* scikit-learn compatibility (134)
* EXPERIMENTAL: incomplete, contributions welcome
* 4 datasets (Adult, German, Bank, Compas) in DataFrame format with protected attributes in the index
* Automatically downloads from openml.org
* 6 group fairness metrics as functions (`statistical_parity_difference`, `disparate_impact_ratio`, `equal_opportunity_difference`, `average_odds_difference`, `average_odds_error`, `between_group_generalized_entropy_error`)
* 2 individual fairness metrics as functions (`generalized_entropy_index` and its variants, `consistency_score`)
* 5 additional metrics as functions (`specificity_score`, `base_rate`, `selection_rate`, `generalized_fpr`, `generalized_fnr`)
* 3 algorithms (`Reweighing`, `AdversarialDebiasing`, `CalibratedEqualizedOdds`)

Fixes
* Fixed deprecation warning/`NotImplementedError` in `StandardDataset` (115)
* Fixed age threshold in `GermanDataset` (129 and 137)
* Corrected privileged/unprivileged attribute values for COMPAS dataset in some demos (138)
* Multiple documentation fixes (114, 124, 153, 155, 157, 158, 159)

New Contributors
autoih, romeokienzler, jimbudarz, stephanNorsten, sethneel, imolloy, guillemarsan, gdequeiroz, chajath, bhavyaghai, Tomcli

0.2.3

=====================

Fixes
-----
* Fixed `fit_predict` arguments in `RejectOptionClassification` (111)
* Removed Orange3 from requirements (113)

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