Semi-Supervised Learning Library (sslearn)

The sslearn library is a Python package for machine learning over Semi-supervised datasets. It is an extension of scikit-learn.

Installation

Dependencies

• joblib >= 1.2.0
• numpy >= 1.23.3
• pandas >= 1.4.3
• scikit_learn >= 1.2.0
• scipy >= 1.10.1
• statsmodels >= 0.13.2
• pytest = 7.2.0 (only for testing)

pip installation

It can be installed using Pypi:

pip install sslearn

Citing

@article{sslearn2025garrido,
    title = {SSLearn: A Semi-Supervised Learning library for Python},
    journal = {SoftwareX},
    volume = {29},
    pages = {102024},
    year = {2025},
    issn = {2352-7110},
    doi = {https://doi.org/10.1016/j.softx.2024.102024},
    author = {José L. Garrido-Labrador and Jesús M. Maudes-Raedo and Juan J. Rodríguez and César I. García-Osorio},
}

Fundings

The research carried out for the development of this software has been partially funded by the Junta de Castilla y León (project BU055P20), by the Ministry of Science and Innovation of Spain (projects PID2020-119894GB-I00 and TED 2021-129485B-C43) and by the project AIM-LAC (EP/S023992 /1). The author has been a beneficiary of the predoctoral scholarship from the Ministry of Education of the Junta de Castilla y León EDU/875/2021.