Licensing Notes

This Package

flaggam is released under the Apache License 2.0 (see LICENSE in the repository root).

The implementation is an independent from-scratch realisation of the method described in the papers listed below. No source code, text, figures, or tables from either paper are reproduced in this repository.

FlagGAM Paper

The FlagGAM method is described in:

Zhao, Z. and Welsch, R. E. (2026). FlagGAM: Rule-Basis Generalized Additive Models for Explainable Tabular Prediction. arXiv:2605.31189.

The preprint PDF (FlagGAM.pdf) is not committed to this repository and is treated as all-rights-reserved. No expression from that document has been reused in this codebase, including documentation strings, comments, or variable names derived from verbatim PDF text.

Univariate Flagging Algorithm (UFA) Paper

The Univariate Flagging Algorithm used in the screening step is described in:

Sheth, M., Gerovitch, A., Welsch, R. E., Markuzon, N. (2019). The Univariate Flagging Algorithm (UFA): An interpretable approach for predictive modeling. PLOS ONE 14(10): e0223161. https://doi.org/10.1371/journal.pone.0223161

This paper is published under the Creative Commons Attribution (CC BY) 4.0 licence. The implementation follows the method as described; no text has been copied verbatim.

Datasets

Dataset licences are the responsibility of the caller. Each dataset loader (shipped in the separate benchmarks plan) documents the applicable licence in its module docstring. Users must verify that their use of any dataset complies with its licence terms before running experiments.