Metadata-Version: 2.4
Name: skfair
Version: 0.1.0
Summary: A package to capture FAIR-compliant provenance for scikit-learn workflows.
Home-page: https://github.com/jjlange/skfair
Author: Justin Lange
Author-email: langejustin@icloud.com
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: scikit-learn
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: joblib
Requires-Dist: pyld
Requires-Dist: requests
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
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# skfair

`skfair` is a Python package that provides a wrapper for scikit-learn estimators to automatically capture FAIR compliant provenance metadata for ML workflows. It packages each training run as a standardised [RO-Crate](https://www.researchobject.org/ro-crate/) research object, making experiments more transparent, reproducible, and interoperable.

<sub>¹ This package is based on a research project conducted at The University of Manchester, 2025.<br/>
Research report: [TODO: add link after submission]</sub>
