The AI Fairness 360 toolkit is an open-source library to help detect and remove bias in machine learning models. The AI Fairness 360 Python package includes a comprehensive set of metrics for datasets and models to test for biases, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
We have developed the package with extensibility in mind. This library is still in development. We encourage the contribution of your datasets, metrics, explainers, and debiasing algorithms.
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Release files for aif360 0.2.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| aif360-0.2.3.tar.gz | 53.3 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| aif360-0.2.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 109.8 MB
Release files / aif360-0.2.3.tar.gz
| Download URL | aif360-0.2.3.tar.gz |
|---|---|
| Size | 53.3 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0.post20191030 requests-toolbelt/0.9.1 tqdm/4.37.0 CPython/3.6.9
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Release files / aif360-0.2.3-py3-none-any.whl
| Download URL | aif360-0.2.3-py3-none-any.whl |
|---|---|
| Size | 56.4 MB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0.post20191030 requests-toolbelt/0.9.1 tqdm/4.37.0 CPython/3.6.9
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