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mlr3pipelines: Preprocessing Operators and Pipelines for 'mlr3'

Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.

Version: 0.7.0
Depends: R (≥ 3.1.0)
Imports: backports, checkmate, data.table, digest, lgr, mlr3 (≥ 0.20.0), mlr3misc (≥ 0.9.0), paradox, R6, withr
Suggests: ggplot2, glmnet, igraph, knitr, lme4, mlbench, bbotk (≥ 0.3.0), mlr3filters (≥ 0.1.1), mlr3learners, mlr3measures, nloptr, quanteda, rmarkdown, rpart, stopwords, testthat, visNetwork, bestNormalize, fastICA, kernlab, smotefamily, evaluate, NMF, MASS, kknn, GenSA, methods, vtreat, future, htmlwidgets, ranger, themis
Published: 2024-09-24
DOI: 10.32614/CRAN.package.mlr3pipelines
Author: Martin Binder [aut, cre], Florian Pfisterer ORCID iD [aut], Lennart Schneider ORCID iD [aut], Bernd Bischl ORCID iD [aut], Michel Lang ORCID iD [aut], Sebastian Fischer ORCID iD [aut], Susanne Dandl [aut], Keno Mersmann [ctb], Maximilian Mücke ORCID iD [ctb]
Maintainer: Martin Binder <mlr.developer at mb706.com>
BugReports: https://github.com/mlr-org/mlr3pipelines/issues
License: LGPL-3
URL: https://mlr3pipelines.mlr-org.com, https://github.com/mlr-org/mlr3pipelines
NeedsCompilation: no
Citation: mlr3pipelines citation info
Materials: README NEWS
CRAN checks: mlr3pipelines results

Documentation:

Reference manual: mlr3pipelines.pdf
Vignettes: Adding new PipeOps (source, R code)

Downloads:

Package source: mlr3pipelines_0.7.0.tar.gz
Windows binaries: r-devel: mlr3pipelines_0.7.0.zip, r-release: mlr3pipelines_0.7.0.zip, r-oldrel: mlr3pipelines_0.7.0.zip
macOS binaries: r-release (arm64): mlr3pipelines_0.7.0.tgz, r-oldrel (arm64): mlr3pipelines_0.7.0.tgz, r-release (x86_64): mlr3pipelines_0.7.0.tgz, r-oldrel (x86_64): mlr3pipelines_0.7.0.tgz
Old sources: mlr3pipelines archive

Reverse dependencies:

Reverse depends: mlr3fda, mlr3torch
Reverse imports: mcboost, mlr3fairness, mlr3shiny, mlr3verse, sense, spFSR
Reverse suggests: counterfactuals, DoubleML, mlr3filters, mlr3fselect, mlr3hyperband, mlr3mbo, mlr3spatiotempcv, mlr3summary, mlr3tuning, mlrintermbo

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.