AIF360
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Trusted-AI
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
https://archive.ics.uci.edu/ml/datasets/student%2Bperformance Potential Tasks: - [ ] Ensure the license permits open source us - [ ] Verify that this dataset is appropriate for fairness tasks and subset it accordingly (removing...
- [ ] [demo_optim_preproc_adult.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/demo_optim_preproc_adult.ipynb) - [ ] [demo_reject_option_classification.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/demo_reject_option_classification.ipynb) - [ ] [demo_reweighing_preproc.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/demo_reweighing_preproc.ipynb) - [ ] [demo_short_gerryfair_test.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/demo_short_gerryfair_test.ipynb)
Make notebooks compatible with Google Colab. This generally involves adding a cell to install the package and download the relevant dataset. See [demo_lime.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/demo_lime.ipynb) for an example. This snippet may be...
dataset location: [https://archive.ics.uci.edu/ml/datasets/diabetes+130-us+hospitals+for+years+1999-2008](https://archive.ics.uci.edu/ml/datasets/diabetes%2B130-us%2Bhospitals%2Bfor%2Byears%2B1999-2008) Potential Tasks: - [ ] Ensure the license permits open source us - [ ] Verify that this dataset is appropriate for fairness tasks and subset it...
Signed-off-by: [email protected] Resolves: #343
folktables (https://github.com/zykls/folktables) is an "improved" version of UCI Adult dataset (which is derived from old US census data). It would be nice to natively incorporate this into the toolkit so...
### Category Datasets ### Why is this issue important At this point in time, AIF360 doesn't support an easy way to download datasets from places like Kaggle. One should manually...
Similar to issues: https://github.com/Trusted-AI/AIF360/issues/341 https://github.com/Trusted-AI/AIF360/issues/342 Goal is to be able to have a simple way to download data from places like UCI from AIF360 directly. This will make it easy...
- [ ] [demo_gerryfair.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/demo_gerryfair.ipynb) - [ ] [demo_json_explainers.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/demo_json_explainers.ipynb) - [ ] [demo_lfr.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/demo_lfr.ipynb) - [x] [demo_lime.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/demo_lime.ipynb)
- [ ] [tutorial_bias_advertising.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/tutorial_bias_advertising.ipynb) - [ ] [tutorial_credit_scoring.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/tutorial_credit_scoring.ipynb) - [ ] [tutorial_medical_expenditure.ipynb](https://github.com/Trusted-AI/AIF360/blob/master/examples/tutorial_medical_expenditure.ipynb)
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A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.