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 [aut, cre], Marc Becker [aut], Bernd Bischl [aut], Giuseppe Casalicchio [aut], Ludwig Bothmann [aut] Maintainer: Susanne Dandl <dandls.datascience at gmail.com> License: LGPL-3 NeedsCompilation: no Language: en-US Materials: README CRAN checks: mlr3summary results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=mlr3summary to link to this page.
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