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mlr3superlearner: Super Learner Fitting and Prediction

An implementation of the Super Learner prediction algorithm from van der Laan, Polley, and Hubbard (2007) <doi:10.2202/1544-6115.1309 using the 'mlr3' framework.

Version: 0.1.2
Depends: mlr3learners
Imports: checkmate, lgr, mlr3, data.table, purrr, cli, glmnet
Suggests: ranger, testthat (≥ 3.0.0)
Published: 2024-09-17
DOI: 10.32614/CRAN.package.mlr3superlearner
Author: Nicholas Williams ORCID iD [aut, cre, cph]
Maintainer: Nicholas Williams <ntwilliams.personal at gmail.com>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mlr3superlearner results

Documentation:

Reference manual: mlr3superlearner.pdf

Downloads:

Package source: mlr3superlearner_0.1.2.tar.gz
Windows binaries: r-devel: mlr3superlearner_0.1.2.zip, r-release: mlr3superlearner_0.1.2.zip, r-oldrel: mlr3superlearner_0.1.2.zip
macOS binaries: r-release (arm64): mlr3superlearner_0.1.2.tgz, r-oldrel (arm64): mlr3superlearner_0.1.2.tgz, r-release (x86_64): mlr3superlearner_0.1.2.tgz, r-oldrel (x86_64): mlr3superlearner_0.1.2.tgz
Old sources: mlr3superlearner archive

Reverse dependencies:

Reverse imports: crumble

Linking:

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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.