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ebm  

Explainable Boosting Machines
View on CRAN: Click here


Download and install ebm package within the R console
Install from CRAN:
install.packages("ebm")

Install from Github:
library("remotes")
install_github("cran/ebm")

Install by package version:
library("remotes")
install_version("ebm", "0.1.0")



Attach the package and use:
library("ebm")
Maintained by
Brandon M. Greenwell
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-03-05
Latest Update: 2025-03-05
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.
How to cite:
Brandon M. Greenwell (2025). ebm: Explainable Boosting Machines. R package version 0.1.0, https://cran.r-project.org/web/packages/ebm. Accessed 16 Jul. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited ebm R package
View ebm citation profile
Other R packages that ebm depends, imports, suggests or enhances
Complete documentation for ebm
Functions, R codes and Examples using the ebm R package
Full ebm package functions and examples
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