Travis CircleCI PyPi scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and is distributed under the 3-Clause BSD license.
The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and since then many volunteers have contributed. See the http://scikit-learn.org
scikit-learn requires:
Scikit-learn 0.20 was the last version to support Python 2.7. scikit-learn 0.21 and later require Python 3.5 or newer.
For running the examples Matplotlib >= 1.5.1 is required. A few examples require scikit-image >= 0.12.3, a few examples require pandas >= 0.18.0.
scikit-learn also uses CBLAS, the C interface to the Basic Linear Algebra Subprograms library. scikit-learn comes with a reference implementation, but the system CBLAS will be detected by the build system and used if present. CBLAS exists in many implementations; see User installation
If you already have a working installation of numpy and scipy,
the easiest way to install scikit-learn is using pip
pip install -U scikit-learn
or conda:
conda install scikit-learn
The documentation includes more detailed Changelog
We welcome new contributors of all experience levels. The scikit-learn community goals are to be helpful, welcoming, and effective. The Important links
You can check the latest sources with the command:
git clone https://github.com/scikit-learn/scikit-learn.git
To learn more about making a contribution to scikit-learn, please see our Testing
After installation, you can launch the test suite from outside the
source directory (you will need to have pytest >= 3.3.0 installed):
pytest sklearn
See the web page Submitting a Pull Request
Before opening a Pull Request, have a look at the full Contributing page to make sure your code complies with our guidelines: Project History
The project was started in 2007 by David Cournapeau as a Google Summer of Code project, and since then many volunteers have contributed. See the Help and Support
If you use scikit-learn in a scientific publication, we would appreciate citations: /yuezht/scikit-learn