mechanism-learn 2.3.2

Mechanism-learn is a simple method to deconfound observational data such that any appropriate machine learning model is forced to learn predictive relationships between effects and their causes, despite the potential presence of multiple unknown and unmeasured confounding. The library is compatible with most existing ML deployments. The library is compatible with most existing ML deployments such as models built with Scikit-learn and Keras.

pip install mechanism-learn

To run the experiment code, please install the mechanism-learn package using the distribution file 'mechanism_learn-2.2.1-py3-none-any.whl' in the 'dist' folder.



In Python, use: import mechanism_learn.pipeline to import the mechanism learning algorithms.



Please note that due to the limit of file size, we cannot attach all experiment data, such as ICH CT scans and the Background-MNIST data. The original ICH data is available at https://physionet.org/content/ct-ich/1.3.1/. For the Background-MNIST data, it is modified from the original MNIST dataset. This semi-synthetic Background MNIST dataset can be generated by using the Python code file: .\test_data\semi_synthetic_data\semi-synthetic_data_gen.py.

Release files for mechanism-learn 2.3.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mechanism-learn 2.3.2
File	Size	Uploaded
mechanism_learn-2.3.2.tar.gz	28.2 kB	Jan 2, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for mechanism-learn 2.3.2
File	Interpreter	ABI	Platform	Reset
mechanism_learn-2.3.2-py3-none-any.whl 23.0 kB Jan 2, 2026	Python 3	none	any	Details

Total release size: 51.1 kB

Release files / mechanism_learn-2.3.2.tar.gz

Download URL	mechanism_learn-2.3.2.tar.gz
Size	28.2 kB
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SHA-256 checksum How to use checksums	`f78e25a589ee444d5937fbc7acb08fafd805e3503344cb9a1f90005a4c1d6162`
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Upload date	Jan 2, 2026
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Uploaded via	`twine/6.2.0 CPython/3.9.23`

Release files / mechanism_learn-2.3.2-py3-none-any.whl

Download URL	mechanism_learn-2.3.2-py3-none-any.whl
Size	23.0 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`e64d3204c024d43ef7f6a5d9a9729227cae6d2c65d41daaaf884f876aa2b03b7`
BLAKE2b-256 checksum How to use checksums	`259677449ea81ccbb28a810ae00bd6f3cc17c5261ad38a76c0aa442d9e5f19fc`
Upload date	Jan 2, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.9.23`