# NOT RUN {
library("mlr3")
task = tsk("pima")$select(c("insulin", "triceps"))
sum(complete.cases(task$data()))
task$missings()
tail(task$data())
po = po("missind")
new_task = po$train(list(task))[[1]]
tail(new_task$data())
# proper imputation + missing indicators
impgraph = list(
po("imputesample"),
po("missind")
) %>>% po("featureunion")
tail(impgraph$train(task)[[1]]$data())
# }
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