Juelich Machine Learning Library
Project description
julearn
About
The Forschungszentrum Jülich Machine Learning Library
Check our full documentation here: https://juaml.github.io/julearn/index.html
It is currently being developed and maintained at the Applied Machine Learning group at Forschungszentrum Juelich, Germany.
Installation
Use pip
to install from PyPI like so:
pip install julearn
You can also install via conda
, like so:
conda install -c conda-forge julearn
Licensing
julearn is released under the AGPL v3 license:
julearn, FZJuelich AML machine learning library. Copyright (C) 2020, authors of julearn.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License along with this program. If not, see http://www.gnu.org/licenses/.
Citing
If you use julearn in a scientific publication, please use the following reference
Hamdan, Sami, Shammi More, Leonard Sasse, Vera Komeyer, Kaustubh R. Patil, and Federico Raimondo. ‘Julearn: An Easy-to-Use Library for Leakage-Free Evaluation and Inspection of ML Models’. arXiv, 19 October 2023. https://doi.org/10.48550/arXiv.2310.12568.
Since julearn is also heavily reliant on scikit-learn, please also cite them: https://scikit-learn.org/stable/about.html#citing-scikit-learn
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