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Dataflow Programming for Machine Learning in R

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The [doc](https://mlr3pipelines.mlr-org.com/reference/mlr_pipeops_encode.html) says that is should encode `character()` columns, but: ``` r library(mlr3) library(mlr3pipelines) data = data.table::data.table(x = letters[1:3], y = factor(letters[1:3])) task = as_task_classif(data, id = "task", target =...

`mlr3` has its test helpers in `inst/testthat/` so other packages can load it and use them (https://github.com/mlr-org/mlr3/tree/main/inst/testthat) It would be convenient if the mlr3pipelines test helpers also lived in `inst`

https://github.com/mlr-org/mlr3pipelines/blob/dae03afd8efa83621a495a058f42cfc2ea8d7357/R/ppl.R#L6 Replace `charcter(1)` with `character(1)`.

This is already fixed in this PR: https://github.com/mlr-org/mlr3pipelines/pull/737

Type: Bug
Priority: Critical
Tag: POFU

check that we are using encapsulate for all pipeop (default) arguments and check functions

``` r library(mlr3proba) #> Loading required package: mlr3 task = tsk('lung') trgs = task$data(cols = task$target_names) trgs #> time status #> 1: 306 TRUE #> 2: 455 TRUE #> 3:...

workshop

In many cases the objects in a graph have some kind of in-place option, and in fact we often explicitly clone objects to avoid this. It is necessary in general,...