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Scikit-learn: Machine Learning in Python

Authors:

Fabian Pedregosa,

Gaël Varoquaux,

Alexandre Gramfort,

Vincent Michel,

Bertrand Thirion,

Olivier Grisel,

Mathieu Blondel,

Peter Prettenhofer,

Vincent Dubourg,

Jake Vanderplas,

Alexandre Passos,

David Cournapeau,

Matthieu Brucher,

Matthieu Perrot,

Édouard DuchesnayAuthors Info & Claims

The Journal of Machine Learning Research, Volume 12

Pages 2825 - 2830

Published: 01 November 2011 Publication History

Abstract

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings. Source code, binaries, and documentation can be downloaded from http://scikit-learn.sourceforge.net.

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Published: 01 November 2011

Published in JMLR Volume 12

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