Metadata-Version: 2.1
Name: hpsklearn-compneurobilbao
Version: 1.0.3
Summary: Hyperparameter Optimization for sklearn, compneurobilbaolab unofficial version.
Home-page: https://github.com/compneurobilbao/hyperopt-sklearn
Author: {James Bergstra, Iñigo Tellaetxe Elorriaga}
Author-email: compneurobilbaolab@gmail.com
License: BSD
Keywords: hyperopt,hyperparameter,sklearn
Platform: Linux
Platform: OS-X
Platform: Windows
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Environment :: Console
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Requires-Python: >=3.9
License-File: LICENSE.txt
Requires-Dist: hyperopt>=0.2.6
Requires-Dist: numpy>=1.26.0
Requires-Dist: scikit-learn>=1.3.0
Requires-Dist: scipy>=1.11.2
Provides-Extra: lightgbm
Requires-Dist: lightgbm>=4.0.0; extra == "lightgbm"
Provides-Extra: testing
Requires-Dist: tox>=4.11.3; extra == "testing"
Provides-Extra: xgboost
Requires-Dist: xgboost>=2.0.0; extra == "xgboost"

# hyperopt-sklearn (CompNeuroBilbao Fork)

## DISCLAIMER
**THIS IS A FORK MADE BY CompNeuroLabBilbao TO PUBLISH THIS PACKAGE TO PyPI IN ORDER TO USE IT IN OTHER PROJECTS, SPECIFICALLY TO ADD IT TO [ageml](https://github.com/compneurobilbao/ageml).**

The functional code in this fork has **NOT** been altered in any way, publishing-related files and this README.md file have been modified.

---
[Hyperopt-sklearn](https://github.com/hyperopt/hyperopt-sklearn) is
[Hyperopt](https://github.com/hyperopt/hyperopt)-based model selection among machine learning algorithms in
[scikit-learn](http://scikit-learn.org/).

See how to use hyperopt-sklearn through [examples](https://hyperopt.github.io/hyperopt-sklearn/#examples).
More examples can be found in the Example Usage section of the SciPy paper:
Komer B., Bergstra J., and Eliasmith C. "Hyperopt-Sklearn: automatic hyperparameter configuration for Scikit-learn" Proc. SciPy 2014. http://conference.scipy.org/proceedings/scipy2014/pdfs/komer.pdf

## Installation

Installation from the GitHub repository is supported using pip:

    pip install git+https://github.com/hyperopt/hyperopt-sklearn
    
Optionally you can install a specific tag, branch or commit:

    pip install git+https://github.com/hyperopt/hyperopt-sklearn@1.0.3
    pip install git+https://github.com/hyperopt/hyperopt-sklearn@master
    pip install git+https://github.com/hyperopt/hyperopt-sklearn@fd718c44fc440bd6e2718ec1442b1af58cafcb18
