Skip to main content

A Python library for training and tuning machine learning models.

Project description



Downloads PyPI License DOI

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 3.7 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 3.7 Python 3.8 Python 3.9–3.10 Python 3.11+
joblib 1.3.2
tqdm 4.66.4
catboost 1.2.7
setuptools 75.1.0
wheel 0.44.0
numpy 1.21.4 >=1.19.5,<2.0.0
pandas 1.1.5 >=1.3.5,<2.2.3
scikit-learn 0.23.2 >=1.0.2,<1.4.0 >=1.0.2,<=1.5.1 1.5.1
scipy 1.4.1 >=1.6.3,<1.11 >=1.6.3,<=1.14.0 1.14.0
imbalanced-learn 0.7.0 0.12.4
scikit-optimize 0.8.1 0.10.2
xgboost 1.6.2 2.1.2

Legend:
✓ – Same as previous version
— – Not applicable or not required

💾 Installation

You can install model_tuner directly from PyPI:

pip install model_tuner

📄 Official Documentation

https://uclamii.github.io/model_tuner

🌐 Website

https://www.mii.ucla.edu/

⚖️ 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      = {0.0.32b},
  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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

model_tuner-0.0.32b0.tar.gz (34.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

model_tuner-0.0.32b0-py3-none-any.whl (33.6 kB view details)

Uploaded Python 3

File details

Details for the file model_tuner-0.0.32b0.tar.gz.

File metadata

  • Download URL: model_tuner-0.0.32b0.tar.gz
  • Upload date:
  • Size: 34.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for model_tuner-0.0.32b0.tar.gz
Algorithm Hash digest
SHA256 cb337c366d2533cc85100d60e9167ab6e5fba8bb353ee82cb8269b6f6681482b
MD5 9f9a75e1410aeb0e153a36654c977351
BLAKE2b-256 ee956654f683d15458aaba14cb8d8a36dac67b5b7cd30a9d55b0e8aca24092da

See more details on using hashes here.

File details

Details for the file model_tuner-0.0.32b0-py3-none-any.whl.

File metadata

  • Download URL: model_tuner-0.0.32b0-py3-none-any.whl
  • Upload date:
  • Size: 33.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for model_tuner-0.0.32b0-py3-none-any.whl
Algorithm Hash digest
SHA256 3011414a834f5f8ba3e56b6e41e4d8ef36d19c041ca3fb3b92149d55f8b02425
MD5 c30ce682180c108e4e7a10458eac2e34
BLAKE2b-256 76636ef97204a73b843f3f580bd2aa202c92a5aac58c254c96d5d10be92b8fcb

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page