This release is a pre-release and may not be stable for production use.
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
Sami Hamdan,Shammi More,Leonard Sasse,Vera Komeyer,Kaustubh R. Patil,Federico Raimondo,for the Alzheimer’s Disease Neuroimaging Initiative,Julearn: an easy-to-use library for leakage-free evaluation and inspection of ML models,Gigabyte,2024 https://doi.org/10.46471/gigabyte.113
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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