TY  - JOUR
TI  - Scikit-learn: Machine Learning in Python
AU  - Fabián Pedregosa
AU  - Gaël Varoquaux
AU  - Alexandre Gramfort
AU  - Vincent Michel
AU  - Bertrand Thirion
AU  - Olivier Grisel
AU  - Mathieu Blondel
AU  - Müller
AU  - Andreas
AU  - Nothman, Joel
AU  - Louppe
AU  - Gilles
AU  - Peter Prettenhofer
AU  - Ron J. Weiss
AU  - Vincent Dubourg
AU  - Jake Vanderplas
AU  - Alexandre Passos
AU  - David Cournapeau
AU  - Matthieu Brucher
AU  - Matthieu Perrot
AU  - Édouard Duchesnay
PY  - 2012
JO  - Open Repository and Bibliography (University of Liège)
DO  - 10.48550/arxiv.1201.0490
UR  - https://doi.org/10.48550/arxiv.1201.0490
AB  - 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.org.
ER  -