Frequently Asked Questions

How to Contribute

Contributions are welcome. The workflow is:

• Check the GitHub issue tracker for “help wanted” items and leave a comment on one you would like to take on so it can be assigned to you.

• Fork the master branch and add your change on a feature branch.

• Open a pull request against the development branch and follow the PR template.

• CI will run the full test suite on your PR. New modules must ship with corresponding tests.

For style conventions, refer to any of the well-established detector modules such as abod.py, hbos.py, or feature_bagging.py.

You are also welcome to open an issue to share ideas or reach the maintainer at zhaoy@cmu.edu.

Inclusion Criteria

Similar to scikit-learn’s inclusion criteria, PyOD prioritizes well-established algorithms. A rule of thumb is at least two years since publication, 50+ citations, and practical usefulness on real-world anomaly detection tasks.

Authors of newly proposed detectors are welcome to contribute their implementations to improve accessibility and reproducibility, provided they can commit to at least two years of maintenance for the contributed model.