Fairness Influence Functions
A Python package for explaining bias in machine learning models based on global sensitivity analysis. Read the paper.
Install
pip install fairxplainer
Other supported libraries can be installed using pip install -r requirements.txt.
Usage
See Python notebook in this folder.
Contact
1 maintainer
Metadata
1 maintainer
Release files for fairxplainer 0.4.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fairxplainer-0.4.0.tar.gz | 29.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fairxplainer-0.4.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 61.7 kB
Release files / fairxplainer-0.4.0.tar.gz
| Download URL | fairxplainer-0.4.0.tar.gz |
|---|---|
| Size | 29.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.16
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Release files / fairxplainer-0.4.0-py3-none-any.whl
| Download URL | fairxplainer-0.4.0-py3-none-any.whl |
|---|---|
| Size | 32.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.8.16
|
