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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 gmail.com>
License: LGPL-3
NeedsCompilation: no
Language: en-US
Materials: README
CRAN checks: mlr3summary results

Documentation:

Reference manual: mlr3summary.pdf

Downloads:

Package source: mlr3summary_0.1.0.tar.gz
Windows binaries: r-devel: mlr3summary_0.1.0.zip, r-release: mlr3summary_0.1.0.zip, r-oldrel: mlr3summary_0.1.0.zip
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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=mlr3summary to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.