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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 "familiar" in publications use:'
type: software
license: EUPL-1.0
title: 'familiar: End-to-End Automated Machine Learning and Model Evaluation'
version: 2.0.2
doi: 10.32614/CRAN.package.familiar
identifiers:
- type: doi
  value: 10.32614/CRAN.package.familiar
abstract: Single unified interface for end-to-end modelling of regression, categorical
  and time-to-event (survival) outcomes. Models created using familiar are self-containing,
  and their use does not require additional information such as baseline survival,
  feature clustering, or feature transformation and normalisation parameters. Model
  performance, calibration, risk group stratification, (permutation) variable importance,
  individual conditional expectation, partial dependence, and more, are assessed automatically
  as part of the evaluation process and exported in tabular format and plotted, and
  may also be computed manually using export and plot functions. Where possible, metrics
  and values obtained during the evaluation process come with confidence intervals.
authors:
- family-names: Zwanenburg
  given-names: Alex
  email: alexander.zwanenburg@nct-dresden.de
  orcid: https://orcid.org/0000-0002-0342-9545
- family-names: Löck
  given-names: Steffen
preferred-citation:
  type: generic
  title: 'familiar: End-to-End Automated Machine Learning and Model Evaluation'
  authors:
  - family-names: Zwanenburg
    given-names: Alex
    email: alexander.zwanenburg@nct-dresden.de
    orcid: https://orcid.org/0000-0002-0342-9545
  - family-names: Löck
    given-names: Steffen
  year: '2025'
  url: https://github.com/oncoray/familiar
  doi: 10.32614/CRAN.package.familiar
repository: https://oncoray.r-universe.dev
repository-code: https://github.com/oncoray/familiar
commit: a7398744ac98cb66f6d4f19c40e5bf54070f638f
url: https://github.com/oncoray/familiar
date-released: '2026-06-01'
contact:
- family-names: Zwanenburg
  given-names: Alex
  email: alexander.zwanenburg@nct-dresden.de
  orcid: https://orcid.org/0000-0002-0342-9545