hyperopt 0.2.7

Hyperopt is a Python library for serial and parallel optimization over awkward search spaces, which may include real-valued, discrete, and conditional dimensions.

Stars: 7226, Watchers: 7226, Forks: 1055, Open Issues: 138

The hyperopt/hyperopt repo was created 13 years ago and the last code push was 5 days ago.
The project is extremely popular with a mindblowing 7226 github stars!

How to Install hyperopt

You can install hyperopt using pip

pip install hyperopt

or add it to a project with poetry

poetry add hyperopt

Package Details

Author

James Bergstra

License

BSD

Homepage

https://hyperopt.github.io/hyperopt

PyPi:

https://pypi.org/project/hyperopt/

GitHub Repo:

https://github.com/hyperopt/hyperopt

Classifiers

• Scientific/Engineering
• Software Development

Related Packages

Errors

A list of common hyperopt errors.

Code Examples

Here are some hyperopt code examples and snippets.

GitHub Issues

The hyperopt package has 138 open issues on GitHub

• scikit-learn compatible meta-estimator
• Security issue in required library networkx
• Recursion error while sampling from custom expression
• When using RandomForestClassifier with hp.choice, get AttributeError: 'RandomForestClassifier' object has no attribute 'estimators_'
• Can't hide logs
• MongoDB error: Unknown option j
• AttributeError with numpy while using HyperoptEstimator
• Proper way to use search_space

See more issues on GitHub