This release is a pre-release and may not be stable for production use.
The model_tuner library is a versatile and powerful tool designed to facilitate the training, tuning, and evaluation of machine learning models. It supports various functionalities such as handling imbalanced data, applying different scaling and imputation techniques, calibrating models, and conducting cross-validation. This library is particularly useful for hyperparameter tuning and ensuring optimal performance across different metrics.
Prerequisites
Before installing model_tuner, ensure your system meets the following requirements:
Python Version
model_tuner requires Python 3.8 or higher. Specific dependency versions vary depending on your Python version.
📦 Dependencies
The following dependencies will be automatically installed for each python version when you install model_tuner via pip:
| Package | Python 3.8 | Python 3.9 | Python 3.10+ |
|---|---|---|---|
joblib |
>=1.3.2,<2.0 |
✓ | ✓ |
tqdm |
>=4.66.4,<5.0 |
✓ | ✓ |
scikit-optimize |
>=0.10.2,<0.11 |
✓ | ✓ |
pandas |
>=1.3.5,<2.2.3 |
✓ | ✓ |
numpy |
>=1.19.5,<2.0.0 |
✓ | >=1.26,<3.0 |
scikit-learn |
>=1.0.2,<1.4.0 |
==1.5.1 |
>=1.6,<1.9 |
scipy |
>=1.6.3,<1.11 |
>=1.6.3,<2.0 |
>=1.14.0,<2.0 |
catboost |
>=1.2.7,<1.2.10 |
✓ | >=1.2.10 |
xgboost |
>=2.1.2,<3.0 |
✓ | >=3.0,<4.0 |
imbalanced-learn |
>=0.12.4,<0.13 |
✓ | >=0.14,<0.15 |
Legend:
✓ -- Same as previous column
💾 Installation
You can install model_tuner directly from PyPI:
pip install model_tuner
📄 Official Documentation
https://uclamii.github.io/model_tuner
🌐 Website
⚖️ License
model_tuner is distributed under the Apache License. See LICENSE for more information.
📚 Citing model_tuner
If you use model_tuner in your research or projects, please consider citing it.
@software{funnell_2024_12727322,
author = {Funnell, Arthur and
Shpaner, Leonid and
Petousis, Panayiotis},
title = {Model Tuner},
month = jul,
year = 2024,
publisher = {Zenodo},
version = {0.0.34b10},
doi = {10.5281/zenodo.12727322},
url = {https://doi.org/10.5281/zenodo.12727322}
}
Support
If you have any questions or issues with model_tuner, please open an issue on this GitHub repository.
Acknowledgements
This work was supported by the UCLA Medical Informatics Institute (MII) and the Clinical and Translational Science Institute (CTSI). Special thanks to Dr. Alex Bui for his invaluable guidance and support, and to Panayiotis Petousis, PhD, for his original contributions to this codebase.
Metadata
Release files for model-tuner 0.0.34b10
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| model_tuner-0.0.34b10.tar.gz | 35.9 kB | Without provenance | Details for model_tuner-0.0.34b10.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| model_tuner-0.0.34b10-py3-none-any.whl | Python 3 | none | any | Details for model_tuner-0.0.34b10-py3-none-any.whl |
Total release size: 71.4 kB
Release files / model_tuner-0.0.34b10.tar.gz
| Download URL | model_tuner-0.0.34b10.tar.gz |
|---|---|
| Size | 35.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
cbddf5627b5836771fd4f74f95ad3c100981bfa64efff7ddda99a4b017b21682
|
|
BLAKE2b-256 checksum How to use checksums |
5bc4a2821e8c0db7485fcfd00c4026ee5cef1721de2d174535928b9b818ee7e4
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.8
|
Release files / model_tuner-0.0.34b10-py3-none-any.whl
| Download URL | model_tuner-0.0.34b10-py3-none-any.whl |
|---|---|
| Size | 35.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
aa91c512a5d3f85560d3679aea8fb80a568c09f634fac1b4f1e9270cc3fb3d94
|
|
BLAKE2b-256 checksum How to use checksums |
ccb713b4d805a39e3bd7e0cb3bf1f791be9cd965d99f719166699fc34a72cd25
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.8
|
Security for model-tuner 0.0.34b10
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.