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Juelich Machine Learning Library

Project description

julearn

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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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