Package: ebm 0.1.0

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. 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.

Authors:Brandon M. Greenwell [aut, cre]

ebm_0.1.0.tar.gz
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ebm.pdf |ebm.html
ebm/json (API)
NEWS

# Install 'ebm' in R:
install.packages('ebm', repos = c('https://bgreenwell.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bgreenwell/ebm/issues

Pkgdown site:https://bgreenwell.github.io

On CRAN:

Conda:

aiblackboxexplainable-aiexplainable-machine-learningexplainable-mlglassboximlinterpretabilityinterpretability-and-explainabilityinterpretableinterpretable-aiinterpretable-machine-learninginterpretable-mlinterpretable-modelsmachine-learningxai

4.60 score 1 stars 5 exports 36 dependencies

Last updated 3 days agofrom:cfcfd3541f. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 06 2025
R-4.5-winOKMar 06 2025
R-4.5-macOKMar 06 2025
R-4.5-linuxOKMar 06 2025
R-4.4-winOKMar 06 2025
R-4.4-macOKMar 06 2025
R-4.4-linuxOKMar 06 2025
R-4.3-winOKMar 06 2025
R-4.3-macOKMar 06 2025

Exports:as.ebmebmgeom_stepribbonGeomStepribboninstall_interpret

Dependencies:clicolorspacefansifarverggplot2gluegtablehereisobandjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigpngR6rappdirsRColorBrewerRcppRcppTOMLreticulaterlangrprojrootscalestibbleutf8vctrsviridisLitewithr

ebm-introduction

Rendered fromebm-rjournal.Rnwusingutils::Sweaveon Mar 06 2025.

Last update: 2025-02-27
Started: 2025-02-27

Introduction to ebm

Rendered fromebm.Rmdusingknitr::rmarkdownon Mar 06 2025.

Last update: 2025-02-24
Started: 2025-02-14