@@ -25575,3 +25575,34 @@ tuning, e.g. Grid Search, Random Search, or Simulated Annealing. Various
termination criteria can be set and combined. The class @code{AutoTuner} provides a
convenient way to perform nested resampling in combination with @code{mlr3}.")
(license license:lgpl3)))
+
+(define-public r-mlr3pipelines
+ (package
+ (name "r-mlr3pipelines")
+ (version "0.3.2")
+ (source (origin
+ (method url-fetch)
+ (uri (cran-uri "mlr3pipelines" version))
+ (sha256
+ (base32
+ "1x738b312mcvb0dif88sv4nlh3y6i47q0wagc5ggyh1hnqjiz71y"))))
+ (build-system r-build-system)
+ (propagated-inputs
+ `(("r-backports" ,r-backports)
+ ("r-checkmate" ,r-checkmate)
+ ("r-data-table" ,r-data-table)
+ ("r-digest" ,r-digest)
+ ("r-lgr" ,r-lgr)
+ ("r-mlr3" ,r-mlr3)
+ ("r-mlr3misc" ,r-mlr3misc)
+ ("r-paradox" ,r-paradox)
+ ("r-r6" ,r-r6)
+ ("r-withr" ,r-withr)))
+ (home-page "https://mlr3pipelines.mlr-org.com/")
+ (synopsis "Preprocessing Operators and Pipelines for @code{mlr3}")
+ (description "@code{mlr3pipelines} enriches @code{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 @code{mlr3} Learners and can therefore be
+resampled, benchmarked, and tuned.")
+ (license license:lgpl3)))