Use two or more tasks in AutoML

[MislavSag]

Use two or more tasks in AutoML

[a-hanf]

mlr3automl adapts to the provided task (the pipeline that is created may be different for different tasks). Also, optimal hyperparameters will depend on the data. I'm not sure I understand your use case, can you elaborate a little bit more on what you want to happen when there are multiple tasks?

I would be happy to have more contributors :) You can create a pull request into the development branch with any new features / bugfixes / etc.

[MislavSag]

It s possible to use more than one task in mlr3 benchmark, for example:

design = benchmark_grid(
  tasks = tsks(c("spam", "german_credit", "sonar")),
  learners = lrns(c("classif.ranger", "classif.rpart", "classif.featureless"),
    predict_type = "prob", predict_sets = c("train", "test")),
  resamplings = rsmps("cv", folds = 3)
)

but this is not possible in AutoML function. I thought it would be very convenient to allow for more than onw task in AutoML. All tasks should be of the same type ofc (for example all should be binary classification).

It seems to me you found workaround to use number of features in mlr3 trafo. It seems there is an simple solution here mlr-org/mlr3tuning#309.