Metadata-Version: 2.1
Name: modelsight
Version: 0.2.0
Summary: Better insights into Machine Learning models performance
License: GNU General Public License v3.0
Author: Francesco Pisu
Requires-Python: >=3.10,<3.11
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Software Development :: Build Tools
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: conda-lock (>=2.1.0,<3.0.0)
Requires-Dist: dynaconf (>=3.1.11,<4.0.0)
Requires-Dist: interpret (>=0.4.2,<0.5.0)
Requires-Dist: matplotlib (>=3.7.1,<4.0.0)
Requires-Dist: mlxtend (>=0.2.2,<0.3.0)
Requires-Dist: pandas (>=2.0.2,<3.0.0)
Requires-Dist: scikit-learn (>=1.2.2,<2.0.0)
Requires-Dist: scikits.bootstrap (>=1.1.0,<2.0.0)
Description-Content-Type: text/markdown

# Modelsight

Better insights into Machine Learning models performance.

Modelsight is a collection of functions that create publication-ready graphics for the visual evaluation of binary classifiers adhering to the scikit-learn interface. 

Modelsight is strongly oriented towards the evaluation of already fitted `ExplainableBoostingClassifier` of the [interpretml](https://github.com/interpretml/interpret) package.

## Installation
```console
$ pip install modelsight
```

## Usage
See the [example](/docs/example.ipynb) notebook. 

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`modelsight` was created by Francesco Pisu. It is licensed under the terms of the GNU General Public License v3.0 license.

## Roadmap
Features:
- [x] Average Receiver-operating characteristic curves
- [ ] Average Precision-recall curves
- [ ] Feature importance (Global explanation)
- [ ] Individualized explanations (Local explanation)

CI/CD:
- [ ] Integration with GH Actions

## Credits

`modelsight` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).

