mlr3: Machine Learning in R - Next Generation

Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.

Version: 0.21.0
Depends: R (≥ 3.1.0)
Imports: R6 (≥ 2.4.1), backports, checkmate (≥ 2.0.0), data.table (≥ 1.15.0), evaluate, future, future.apply (≥ 1.5.0), lgr (≥ 0.3.4), mlbench, mlr3measures (≥ 1.0.0), mlr3misc (≥ 0.15.0), parallelly, palmerpenguins, paradox (≥ 1.0.1), uuid
Suggests: Matrix, callr, codetools, datasets, future.callr, mlr3data, progressr, remotes, RhpcBLASctl, rpart, testthat (≥ 3.1.0)
Published: 2024-09-24
DOI: 10.32614/CRAN.package.mlr3
Author: Michel Lang ORCID iD [aut], Bernd Bischl ORCID iD [aut], Jakob Richter ORCID iD [aut], Patrick Schratz ORCID iD [aut], Giuseppe Casalicchio ORCID iD [ctb], Stefan Coors ORCID iD [ctb], Quay Au ORCID iD [ctb], Martin Binder [aut], Florian Pfisterer ORCID iD [aut], Raphael Sonabend ORCID iD [aut], Lennart Schneider ORCID iD [ctb], Marc Becker ORCID iD [cre, aut], Sebastian Fischer ORCID iD [aut], Lona Koers [ctb]
Maintainer: Marc Becker <marcbecker at posteo.de>
BugReports: https://github.com/mlr-org/mlr3/issues
License: LGPL-3
URL: https://mlr3.mlr-org.com, https://github.com/mlr-org/mlr3
NeedsCompilation: no
Citation: mlr3 citation info
Materials: README NEWS
In views: MachineLearning
CRAN checks: mlr3 results

Documentation:

Reference manual: mlr3.pdf

Downloads:

Package source: mlr3_0.21.0.tar.gz
Windows binaries: r-devel: mlr3_0.21.0.zip, r-release: mlr3_0.21.0.zip, r-oldrel: mlr3_0.21.0.zip
macOS binaries: r-release (arm64): mlr3_0.21.0.tgz, r-oldrel (arm64): mlr3_0.21.0.tgz, r-release (x86_64): mlr3_0.21.0.tgz, r-oldrel (x86_64): mlr3_0.21.0.tgz
Old sources: mlr3 archive

Reverse dependencies:

Reverse depends: GenericML, MantaID, mlr3cluster, mlr3db, mlr3fda, mlr3fselect, mlr3learners, mlr3spatial, mlr3spatiotempcv, mlr3torch, mlr3tuning, mlr3verse, SIAMCAT, spFSR
Reverse imports: BioM2, cpi, DoubleML, gKRLS, highMLR, mcboost, mlr3batchmark, mlr3fairness, mlr3filters, mlr3hyperband, mlr3mbo, mlr3oml, mlr3pipelines, mlr3resampling, mlr3shiny, mlr3summary, mlr3superlearner, mlr3tuningspaces, sense
Reverse suggests: condvis2, counterfactuals, DALEXtra, drape, explainer, FACT, iml, miesmuschel, mlr3benchmark, mlr3data, mlr3viz, mlrintermbo, vetiver, vivid
Reverse enhances: vip

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