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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "ebm" in publications use:'
type: software
license: MIT
title: 'ebm: Explainable Boosting Machines'
version: 0.1.0
doi: 10.32614/CRAN.package.ebm
abstract: An interface to the 'Python' 'InterpretML' framework for fitting explainable
  boosting machines (EBMs); see Nori et al. (2019) <https://doi.org/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:
- family-names: Greenwell
  given-names: Brandon M.
  email: greenwell.brandon@gmail.com
  orcid: https://orcid.org/0000-0002-8120-0084
repository: https://bgreenwell.r-universe.dev
repository-code: https://github.com/bgreenwell/ebm
commit: cfcfd3541fe8698eff35a8f80940a61f7373f3a1
url: https://bgreenwell.github.io/ebm/
contact:
- family-names: Greenwell
  given-names: Brandon M.
  email: greenwell.brandon@gmail.com
  orcid: https://orcid.org/0000-0002-8120-0084