mlr3summary: Model and Learner Summaries for 'mlr3'

Concise and interpretable summaries for machine learning models and learners of the 'mlr3' ecosystem. The package takes inspiration from the summary function for (generalized) linear models but extends it to non-parametric machine learning models, based on generalization performance, model complexity, feature importances and effects, and fairness metrics.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: backports, checkmate (≥ 2.0.0), data.table, mlr3 (≥ 0.12.0), mlr3misc, cli, future.apply (≥ 1.5.0)
Suggests: testthat (≥ 3.1.0), iml, mlr3pipelines, mlr3fairness, mlr3learners, fastshap, ranger, rpart
Published: 2024-04-24
DOI: 10.32614/CRAN.package.mlr3summary
Author: Susanne Dandl ORCID iD [aut, cre], Marc Becker ORCID iD [aut], Bernd Bischl ORCID iD [aut], Giuseppe Casalicchio ORCID iD [aut], Ludwig Bothmann ORCID iD [aut]
Maintainer: Susanne Dandl <dandls.datascience at>
License: LGPL-3
NeedsCompilation: no
Language: en-US
Materials: README
CRAN checks: mlr3summary results


Reference manual: mlr3summary.pdf


Package source: mlr3summary_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mlr3summary_0.1.0.tgz, r-oldrel (arm64): mlr3summary_0.1.0.tgz, r-release (x86_64): mlr3summary_0.1.0.tgz, r-oldrel (x86_64): mlr3summary_0.1.0.tgz


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