Running examples in ‘mlr3pipelines-Ex.R’ failed
The error most likely occurred in:

> ### Name: mlr_pipeops_imputelearner
> ### Title: Impute Features by Fitting a Learner
> ### Aliases: mlr_pipeops_imputelearner PipeOpImputeLearner
> 
> ### ** Examples
> 
> ## Don't show: 
> if (requireNamespace("rpart")) (if (getRversion() >= "3.4") withAutoprint else force)({ # examplesIf
+ ## End(Don't show)
+ library("mlr3")
+ 
+ task = tsk("pima")
+ task$missings()
+ 
+ po = po("imputelearner", lrn("regr.rpart"))
+ new_task = po$train(list(task = task))[[1]]
+ new_task$missings()
+ 
+ # '$state' of the "regr.rpart" Learner, trained to predict the 'mass' column:
+ po$state$model$mass
+ 
+ library("mlr3learners")
+ # to use the "regr.kknn" Learner, prefix it with its own imputation method!
+ # The "imputehist" PipeOp is used to train "regr.kknn"; predictions of this
+ # trained Learner are then used to impute the missing values in the Task.
+ po = po("imputelearner",
+   po("imputehist") %>>% lrn("regr.kknn")
+ )
+ 
+ new_task = po$train(list(task = task))[[1]]
+ new_task$missings()
+ ## Don't show: 
+ }) # examplesIf
> library("mlr3")
> task = tsk("pima")
> task$missings()
diabetes      age  glucose  insulin     mass pedigree pregnant pressure 
       0        0        5      374       11        0        0       35 
 triceps 
     227 
> po = po("imputelearner", lrn("regr.rpart"))
> new_task = po$train(list(task = task))[[1]]
> new_task$missings()
diabetes      age pedigree pregnant  glucose  insulin     mass pressure 
       0        0        0        0        0        0        0        0 
 triceps 
       0 
> po$state$model$mass
$model
n= 757 

node), split, n, deviance, yval
      * denotes terminal node

 1) root 757 36254.3300 32.45746  
   2) triceps< 25.5 219  5537.6560 27.93196  
     4) triceps< 20.5 144  3140.7800 26.68333 *
     5) triceps>=20.5 75  1741.3150 30.32933  
      10) pressure< 83 64  1081.6090 29.37813 *
      11) pressure>=83 11   264.8855 35.86364 *
   3) triceps>=25.5 538 24405.7800 34.29963  
     6) triceps< 35.5 380 14414.2500 32.50474  
      12) pressure< 74.5 223  6772.1180 31.49013  
        24) glucose< 73.5 8    44.1000 24.20000 *
        25) glucose>=73.5 215  6287.0300 31.76140  
          50) pregnant>=0.5 190  4822.6790 31.28947 *
          51) pregnant< 0.5 25  1100.4420 35.34800 *
      13) pressure>=74.5 157  7086.5100 33.94586  
        26) insulin< 187 122  4736.5000 33.05656 *
        27) insulin>=187 35  1917.2070 37.04571 *
     7) triceps>=35.5 158  5822.9770 38.61646  
      14) pregnant>=1.5 92  2351.3170 37.02174 *
      15) pregnant< 1.5 66  2911.5580 40.83939 *

$param_vals
$param_vals$xval
[1] 0


$log
Empty data.table (0 rows and 3 cols): stage,class,msg

$train_time
[1] 0.016

$task_hash
[1] "a666d2778d446faf"

$feature_names
[1] "age"      "glucose"  "insulin"  "pedigree" "pregnant" "pressure" "triceps" 

$validate
NULL

$mlr3_version
[1] ‘0.23.0’

$data_prototype
Empty data.table (0 rows and 8 cols): .impute_col,age,glucose,insulin,pedigree,pregnant...

$task_prototype
Empty data.table (0 rows and 8 cols): .impute_col,age,glucose,insulin,pedigree,pregnant...

$train_task
<TaskRegr:imputing> (768 x 8)
* Target: .impute_col
* Properties: -
* Features (7):
  - dbl (7): age, glucose, insulin, pedigree, pregnant, pressure,
    triceps

attr(,"class")
[1] "learner_state" "list"         
> library("mlr3learners")
> po = po("imputelearner", po("imputehist") %>>% lrn("regr.kknn"))
Error in dictionary_retrieve_item(self, key, .dicts_suggest) : 
  Element with key 'regr.kknn' not found in DictionaryLearner! Did you mean 'regr.nnet'?
Calls: <Anonymous> ... dictionary_get -> dictionary_retrieve_item -> stopf
Execution halted