https://github.com/bgreenwell/ebm

Explainable Boosting Machines
https://github.com/bgreenwell/ebm

ai blackbox explainable-ai explainable-machine-learning explainable-ml glassbox iml interpretability interpretability-and-explainability interpretable interpretable-ai interpretable-machine-learning interpretable-ml interpretable-models machine-learning xai

Last synced: 11 days ago
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Explainable Boosting Machines

• Host: GitHub
• URL: https://github.com/bgreenwell/ebm
• Owner: bgreenwell
• License: other
• Created: 2025-02-09T21:12:28.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2025-03-06T01:42:45.000Z (2 months ago)
• Last Synced: 2025-05-07T20:37:08.436Z (11 days ago)
• Topics: ai, blackbox, explainable-ai, explainable-machine-learning, explainable-ml, glassbox, iml, interpretability, interpretability-and-explainability, interpretable, interpretable-ai, interpretable-machine-learning, interpretable-ml, interpretable-models, machine-learning, xai
• Language: R
• Homepage: https://bgreenwell.github.io/ebm/
• Size: 44.5 MB
• Stars: 3
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS.md
  • License: LICENSE

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README

        
# ebm

[![CRAN status](https://www.r-pkg.org/badges/version/ebm)](https://CRAN.R-project.org/package=ebm)

[![R-CMD-check](https://github.com/bgreenwell/ebm/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/bgreenwell/ebm/actions/workflows/R-CMD-check.yaml)

[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)

A [reticulate](https://rstudio.github.io/reticulate/)-powered interface to the Python [InterpretML](https://interpret.ml/) framework for fitting [explainable boosting machines](https://doi.org/10.48550/arXiv.1909.09223) (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

You can install the **ebm** package from either CRAN (stable) or GitHub (development):

```r

# Install the latest stable version from CRAN:

install.packages("ebm")

# Install the latest development version from GitHub:

if (!requireNamespace("remotes")) {

  install.packages("remotes")

}

remotes::install_github("bgreenwell/ebm")

```

# Usage

For a thorough overview of using the **ebm** package, see [this article](https://bgreenwell.github.io/ebm/articles/RJwrapper.pdf).