mlr3pipelines (0.1.1)

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.

Maintainer: Martin Binder
Author(s): Martin Binder [aut, cre], Florian Pfisterer [aut] (<>), Bernd Bischl [aut] (<>), Michel Lang [aut] (<>), Susanne Dandl [aut]

License: LGPL-3

Uses: backports, checkmate, data.table, digest, mlr3, mlr3misc, paradox, R6, withr, fastICA, ggplot2, igraph, kernlab, lme4, mlbench, rpart, glmnet, testthat, nloptr, knitr, rmarkdown, visNetwork, smotefamily, bestNormalize, lgr, mlr3learners, mlr3filters
Reverse depends: mlr3verse

Released about 1 month ago.