Description
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.
README.md
ebm
A reticulate-powered interface to the Python InterpretML framework for fitting explainable boosting machines (EBMs). 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.
Installation
Currently, you can only install the ebm package from GitHub (coming soon to CRAN):
# install.packages("remotes")
remotes::install_github("bgreenwell/ebm")
Usage
For a thorough overview of using the ebm package, see this article.