Gklr

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<!-- PROJECT LOGO --> <br /> <div align="center"> <!-- <a href="https://github.com/JoseAngelMartinB/gklr"> <img src="images/logo.png" alt="Logo" width="80" height="80"> </a> --> <h3 align="center">GKLR</h3> <p align="center"> Generalized Kernel Logistic Regression <br /> <a href="https://gklr.joseangelmartin.com"><strong>Explore the docs »</strong></a> <br /> <br /> <a href="https://github.com/JoseAngelMartinB/gklr/blob/main/notebooks/gklr_LPMC.ipynb">View Demo</a> · <a href="https://github.com/JoseAngelMartinB/gklr/issues">Report Bug</a> · <a href="https://github.com/JoseAngelMartinB/gklr/issues">Request Feature</a> </p> </div>

Description

Generalized Kernel Logistic Regression.

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Installation

It is possible to install the gklr package using pip

pip install gklr

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Authors

GKLR was mainly developed by José Ángel Martín Baos from the University of Castilla-La Mancha (JoseAngel.Martin@uclm.es). The main authors of this package are listed in the AUTHORS file.

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Known Issues

There are no known issues at this moment.

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License

GKLR is distributed under the MIT License. See LICENSE for more information.

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Citation

If you found this repository useful, you can acknowledge the authors by citing:

• José Ángel Martín-Baos, Ricardo García-Ródenas, Luis Rodriguez-Benitez, Michel Bierlaire (2025). Scalable kernel logistic regression with Nyström approximation: Theoretical analysis and application to discrete choice modelling. Neurocomputing 617, 128975. DOI: 10.1016/j.neucom.2024.128975