julearn 0.3.6.dev33

Juelich Machine Learning Library

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