 | |
| Original author(s) | David Cournapeau |
|---|---|
| Initial release | June 2007 |
| Stable release | 1.5.2[1]
/ 11 September 2024 |
| Repository | |
| Written in | Python, Cython, C and C++[2] |
| Operating system | Linux, macOS, Windows |
| Type | Library for machine learning |
| License | New BSD License |
| Website | scikit-learn |
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language.[3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy. Scikit-learn is a NumFOCUS fiscally sponsored project.[4]
- ^ "Release 1.5.2". 11 September 2024. Retrieved 26 September 2024.
- ^ "The scikit-learn Open Source Project on Open Hub: Languages Page". Open Hub. Retrieved 14 July 2018.
- ^ Fabian Pedregosa; Gaël Varoquaux; Alexandre Gramfort; Vincent Michel; Bertrand Thirion; Olivier Grisel; Mathieu Blondel; Peter Prettenhofer; Ron Weiss; Vincent Dubourg; Jake Vanderplas; Alexandre Passos; David Cournapeau; Matthieu Perrot; Édouard Duchesnay (2011). "scikit-learn: Machine Learning in Python". Journal of Machine Learning Research. 12: 2825–2830.
- ^ "NumFOCUS Sponsored Projects". NumFOCUS. Retrieved 2021-10-25.