This release is a pre-release and may not be stable for production use.
Welcome to Model Metrics! Model Metrics is a versatile Python library designed to streamline the evaluation and interpretation of machine learning models. It provides a robust framework for generating predictions, computing model metrics, analyzing feature importance, and visualizing results. Whether you're working with SHAP values, model coefficients, confusion matrices, ROC curves, precision-recall plots, and other key performance indicators.
Prerequisites
Before you install model_metrics, ensure your system meets the following requirements:
Python: Version3.8or higher.
Additionally, model_metrics depends on the following packages, which will be automatically installed when you install model_metrics:
matplotlib: version3.5.3or higher, but capped below3.11matplotlib-venn: version1.0.0or higher, but capped at1.1.2numpy: version1.21.6or higher, but capped below2.2pandas: version1.3.5or higher, but capped below2.3plotly: version5.18.0or higher, but capped below5.25scikit-learn: version1.0.2or higherscipy: version1.7.3or higherstatsmodels: version0.13or higher, but capped below0.15shap: version0.41.0or higher, but capped below0.53tqdm: version4.66.4or higher
💾 Installation
To install model_metrics, simply run the following command in your terminal:
pip install model_metrics
📄 Official Documentation
https://lshpaner.github.io/model_metrics_docs
🌐 Authors' Website(s)
🙏 Acknowledgements
Gratitude goes to Dr. Ebrahim Tarshizi for his mentorship during the University of San Diego M.S. Applied Data Science Program, as well as the Shiley-Marcos School of Engineering for its support.
Special thanks to Dr. Alex Bui, and to Panayiotis Petousis, PhD, and Arthur Funnell for their invaluable guidance and their exceptional teamwork in maintaining a strong data science infrastructure at UCLA CTSI. Their leadership and support have helped foster the kind of collaborative environment that makes work like this possible. Additional thanks to all who offered guidance and encouragement throughout the development of this library. This project reflects a shared commitment to knowledge sharing, teamwork, and advancing model evaluation practices.
⚖️ License
model_metrics is distributed under the MIT License. See LICENSE for more information.
⚓ Support
If you have any questions or issues with model_metrics, please open an issue on this GitHub repository.
📚 Citing model_metrics
If you use model_metrics in your research or projects, please consider citing it.
@software{shpaner_2025_14879819,
author = {Shpaner, Leonid and Funnell, Arthur},
title = {Model Metrics},
month = feb,
year = 2025,
publisher = {Zenodo},
version = {0.0.6a10},
doi = {10.5281/zenodo.14879819},
url = {https://doi.org/10.5281/zenodo.14879819}
}
2 maintainers
Metadata
2 maintainers
Release files for model-metrics 0.0.6a10
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