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: 0.8.0 Depends: R (≥ 3.3.0) Imports: backports, checkmate, data.table, digest, lgr, mlr3 (≥ 0.20.0), mlr3misc (≥ 0.17.0), paradox, R6, withr Suggests: ggplot2, glmnet, igraph, knitr, lme4, mlbench, bbotk (≥ 0.3.0), mlr3filters (≥ 0.8.1), mlr3learners, mlr3measures, nloptr, quanteda, rmarkdown, rpart, stopwords, testthat, visNetwork, bestNormalize, fastICA, kernlab, smotefamily, evaluate, NMF, MASS, GenSA, methods, vtreat, future, htmlwidgets, ranger, themis Published: 2025-06-17 DOI: 10.32614/CRAN.package.mlr3pipelines Author: Martin Binder [aut, cre], Florian Pfisterer [aut], Lennart Schneider [aut], Bernd Bischl [aut], Michel Lang [aut], Sebastian Fischer [aut], Susanne Dandl [aut], Keno Mersmann [ctb], Maximilian Mücke [ctb], Lona Koers [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: Downloads: 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, mlr3tuningspaces, mlrintermbo Linking:Please use the canonical form https://CRAN.R-project.org/package=mlr3pipelines to link to this page.
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