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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 [aut], Lennart Schneider [aut], Bernd Bischl [aut], Michel Lang [aut], Sebastian Fischer [aut], Susanne Dandl [aut], Keno Mersmann [ctb], Maximilian Mücke [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 |
Reference manual: | mlr3pipelines.pdf |
Vignettes: |
Adding new PipeOps (source, R code) |
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 depends: | mlr3fda, mlr3torch |
Reverse imports: | mcboost, mlr3fairness, mlr3shiny, mlr3verse, sense, spFSR |
Reverse suggests: | counterfactuals, DoubleML, mlr3filters, mlr3fselect, mlr3hyperband, mlr3mbo, mlr3spatiotempcv, mlr3summary, mlr3tuning, mlrintermbo |
Please use the canonical form https://CRAN.R-project.org/package=mlr3pipelines 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.