Metadata-Version: 2.1
Name: mlconfound
Version: 0.20.1
Summary: Tools for analyzing and quantifying effects of counfounder variables on machine learning model predictions.
Home-page: https://mlconfound.readthedocs.io
License: GPL-3.0-or-later
Keywords: machine learning,predictive modelling,confounding bias,conditional independence,confounder test
Author: Tamas Spisak
Author-email: tamas.spisak@uni-due.de
Requires-Python: >=3.7,<3.10
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Dist: dot2tex (>=2.11.3)
Requires-Dist: graphviz (>=0.17)
Requires-Dist: joblib (>=1.0.1)
Requires-Dist: numpy (>=1.21.1)
Requires-Dist: pandas (>=1.3.1)
Requires-Dist: pygam (==0.8.0)
Requires-Dist: scipy (>=1.7.1)
Requires-Dist: seaborn (>=0.11.1)
Requires-Dist: statsmodels (>=0.12.2)
Requires-Dist: tqdm (>=4.62.0)
Project-URL: Documentation, https://mlconfound.readthedocs.io
Project-URL: Repository, https://github.com/pni-lab/mlconfound
Description-Content-Type: text/markdown

# mlconfound
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[![arXiv](https://img.shields.io/badge/arXiv-2111.00814-<COLOR>.svg)](https://arxiv.org/abs/2111.00814)
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/pni-lab/mlconfound/master?labpath=notebooks%2Fquickstart.ipynb)

Tools for analyzing and quantifying effects of counfounder variables on machine learning model predictions.
## Install
````
pip install mlconfound
````

## Usage

````
# y   : prediction target
# yhat: prediction
# c   : confounder

from mlconfound.stats import partial_confound_test

partial_confound_test(y, yhat, c)
````

Run the quickstart notebook in Binder: [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/pni-lab/mlconfound/master?labpath=notebooks%2Fquickstart.ipynb)

Read the docs for more details.

## Documentation [![Documentation Status](https://readthedocs.org/projects/mlconfound/badge/?version=latest)](https://mlconfound.readthedocs.io/en/latest/?badge=latest)
https://mlconfound.readthedocs.io

## Citation
T. Spisak, Statistical quantification of confounding bias in predictive modelling, preprint on [arXiv:2111.00814](http://arxiv-export-lb.library.cornell.edu/abs/2111.00814), 2021.

