ebm-package {ebm} | R Documentation |
ebm: Explainable Boosting Machines
Description
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.
Author(s)
Maintainer: Brandon M. Greenwell greenwell.brandon@gmail.com (ORCID)
See Also
Useful links:
[Package ebm version 0.1.0 Index]