Scikit
swMATH ID: | 8058 |
Software Authors: | Pedregosa, Fabian; Varoquaux, Gaël; Gramfort, Alexandre; Michel, Vincent; Thirion, Bertrand; Grisel, Olivier; Blondel, Mathieu; Prettenhofer, Peter; Weiss, Ron; Dubourg, Vincent; Vanderplas, Jake; Passos, Alexandre; Cournapeau, David; Brucher, Matthieu; Perrot, Matthieu; Duchesnay, Édouard |
Description: | Scikit-learn: machine learning in python. 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 url{http://scikit-learn.sourceforge.net}. |
Homepage: | http://scikit-learn.org/stable/ |
Dependencies: | Python |
Keywords: | Python; supervised learning; unsupervised learning; model selection |
Related Software: | Python; SciPy; TensorFlow; UCI-ml; GitHub; NumPy; Adam; PyTorch; Keras; Matplotlib; R; PRMLT; XGBoost; ImageNet; ElemStatLearn; LIBSVM; MNIST; pandas; Gurobi; word2vec |
Cited in: | 827 Documents |
Standard Articles
1 Publication describing the Software, including 1 Publication in zbMATH | Year |
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Scikit-learn: machine learning in Python. Zbl 1280.68189 Pedregosa, Fabian; Varoquaux, Gaël; Gramfort, Alexandre; Michel, Vincent; Thirion, Bertrand; Grisel, Olivier; Blondel, Mathieu; Prettenhofer, Peter; Weiss, Ron; Dubourg, Vincent; Vanderplas, Jake; Passos, Alexandre; Cournapeau, David; Brucher, Matthieu; Perrot, Matthieu; Duchesnay, Édouard |
2011
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Cited by 2,542 Authors
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