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: | 0.7.2 |
| Depends: | R (≥ 3.1.0) |
| Imports: | backports,checkmate,data.table,digest,lgr,mlr3 (≥0.20.0),mlr3misc (≥ 0.16.0),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,kknn,GenSA, methods,vtreat,future,htmlwidgets,ranger,themis |
| Published: | 2025-03-07 |
| 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: | READMENEWS |
| CRAN checks: | mlr3pipelines results |