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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
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Submitted on : Wednesday, June 20, 2018 - 5:25:21 PM
Last modification on : Wednesday, March 23, 2022 - 3:51:06 PM
Long-term archiving on: : Tuesday, September 25, 2018 - 9:38:47 PM


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  • HAL Id : hal-01514059, version 3



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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