Project Information

This section provides details about the glmpynet project, including its dependencies, citation guidance, and how to contribute.

Dependencies

The glmpynet library relies on a minimal set of open-source Python packages, installed automatically when you install glmpynet via pip.

numpy

For efficient numerical operations and array handling.

The glmnetpp C++ library is the core dependency, providing high-performance regularized logistic regression. It is precompiled in the glmpynet package, requiring no additional setup for users.

Citation

If you use glmpynet in your work, please cite it as:

glmpynet: A scikit-learn-compatible Python package for regularized logistic regression using the glmnetpp C++ library. Available at https://github.com/hrolfrc/glmpynet.

You may also cite the glmnetpp library, which glmpynet builds upon, following its citation guidelines (see glmnet’s R documentation or online resources).

Contributing & License

Contributing

glmpynet is open source, and contributions are welcome. Visit the GitHub repository (https://github.com/hrolfrc/glmpynet) to: - Report bugs or suggest features via the issue tracker. - Submit pull requests with code, tests, or documentation improvements. - Review ROADMAP.md and DEVELOPMENT_PLAN.md for project goals and tasks.

See CONTRIBUTING.md in the repository for specific guidelines.

License

glmpynet is distributed under the GNU General Public License version 2 (GPL-2.0-only). This copyleft license requires derivative works to be licensed under the same terms. See the LICENSE file in the repository for the full text.