scikit-learn 1.8.0

A set of python modules for machine learning and data mining

Stars: 65069, Watchers: 65069, Forks: 26706, Open Issues: 2131

The scikit-learn/scikit-learn repo was created 15 years ago and the last code push was 3 hours ago.
The project is extremely popular with a mindblowing 65069 github stars!

How to Install scikit-learn

You can install scikit-learn using pip

pip install scikit-learn

or add it to a project with poetry

poetry add scikit-learn

Package Details

Author

None

License

None

Homepage

None

PyPi:

https://pypi.org/project/scikit-learn/

GitHub Repo:

https://github.com/scikit-learn/scikit-learn

Classifiers

• Scientific/Engineering
• Software Development

Related Packages

Errors

A list of common scikit-learn errors.

Code Examples

Here are some scikit-learn code examples and snippets.

GitHub Issues

The scikit-learn package has 2131 open issues on GitHub

• Improve contribution guidelines to make it easier for maintainers to assess the user facing value of issues/PRs
• DOC Add statement on supported versions for array API
• Fix response_method='auto' for clusterers in DecisionBoundaryDisplay
• Analyze the practical relevance importance of GBT hyperparameters
• MAINT Simpler array API lock file config
• BUG: error message raised by validate_params cannot pass check_estimator
• Improve wording in common pitfalls documentation
• DOC: add warm_start manual grid search example for forests
• Fix KNN failure on non-numeric labels with brute algorithm and p=1
• FIX: fix boundary 0-weight edge-case in _weighted_percentile
• ENH update code to check response values of an estimator
• DOC: improve clarity and reproducibility in classification probability example
• CI Migrate Linux_Nightly build to GHA
• MAINT: Remove broken bench_multilabel_metrics.py
• Support clusterers in DecisionBoundaryDisplay

See more issues on GitHub