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Pycobra: A Python Toolbox for Ensemble Learning and Visualisation

Benjamin Guedj 1 Bhargav Srinivasa Desikan 1
1 MODAL - MOdel for Data Analysis and Learning
LPP - Laboratoire Paul Painlevé - UMR 8524, Université de Lille, Sciences et Technologies, Inria Lille - Nord Europe, METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694, Polytech Lille - École polytechnique universitaire de Lille
Abstract : We introduce pycobra, a Python library devoted to ensemble learning (regression and classification) and visualisation. Its main assets are the implementation of several ensemble learning algorithms, a flexible and generic interface to compare and blend any existing machine learning algorithm available in Python libraries (as long as a predict method is given), and visualisation tools such as Voronoi tessellations. pycobra is fully scikit-learn compatible and is released under the MIT open-source license. pycobra can be down-loaded from the Python Package Index (PyPi) and Machine Learning Open Source Software (MLOSS). The current version (along with Jupyter notebooks, extensive documentation, and continuous integration tests) is available at https://github.com/bhargavvader/pycobra.
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https://hal.inria.fr/hal-01514059
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Submitted on : Wednesday, June 20, 2018 - 5:25:21 PM
Last modification on : Friday, November 27, 2020 - 2:18:02 PM
Long-term archiving on: : Tuesday, September 25, 2018 - 9:38:47 PM

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Benjamin Guedj, Bhargav Srinivasa Desikan. Pycobra: A Python Toolbox for Ensemble Learning and Visualisation. Journal of Machine Learning Research, Microtome Publishing, 2018, 18, pp.1 - 5. ⟨hal-01514059v3⟩

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