ebm
Explainable Boosting Machines
An interface to the 'Python' 'InterpretML' framework for fitting explainable boosting machines (EBMs); see Nori et al. (2019) <doi:10.48550/arXiv.1909.09223> for details. EBMs are a modern type of generalized additive model that use tree-based, cyclic gradient boosting with automatic interaction detection. They are often as accurate as state-of-the-art blackbox models while remaining completely interpretable.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling source/ R- | ebm_0.1.0.tar.gz |
856.5 KiB |
0.1.0 |
latest source/ R- | ebm_0.1.0.tar.gz |
856.5 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | ebm_0.1.0.zip |
504.9 KiB |
Dependencies (latest)
Imports
- reticulate
- ggplot2 (>= 0.9.0)
- lattice