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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 |
| 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:
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.
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