Tools for analyzing and quantifying effects of counfounder variables on machine learning model predictions.
Project description
mlconfound
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:
Read the docs for more details.
Documentation
https://mlconfound.readthedocs.io
Citation
T. Spisak, Statistical quantification of confounding bias in predictive modelling, preprint on arXiv:2111.00814, 2021.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
mlconfound-0.21.3.tar.gz
(22.7 kB
view hashes)
Built Distribution
Close
Hashes for mlconfound-0.21.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8c04ddb8cd271a7024897cdf0128427d28b168f1ec166e130a47d5a68a838846 |
|
MD5 | fc63bdea444b7da20ff76c6561987506 |
|
BLAKE2b-256 | cf11d4399523d7aef43eef31290907d104965d1e2ba24a526d4fcb75561f0c4e |