Extend PipeOpLearnerCV for other resamplings

[pfistfl]

levels = c("cv", "insample") is currently very limited and not flexibly extensible i.e. for mlr3spatiotmpcv resamplings.
Might need some mechanism to allow a subset of mlr_resamplings

[mb706]

problem to anticipate here is that not all resamplings create a prediction for every input row (#216 will get relevant here), and some may create multiple predictios (does mean averaging usually make sense?)

[pfistfl]

This is rather urgent though, as the current version blocks e.g. mlr3spatiotempcv resampling and makes the PO non-extensible which popped up in at least one project.
We could perhaps allow all mlr_resamplings and just document that this might break?

In general, another possibility would be to

• in case of e.g. holdout, just fill up the rest of the predictions with ǸA`
• in case multiple predictions exist just create additional columns as needed.
  the current return format is a data.table anyway.

[mb706]

filling with NA is probably a good idea. I don't like multiple columns because the number of output columns must be the same in train() and predict. I guess if it's supposed to be quick we can just mean(). It would be nice though to do something sensible with se and prob. (But I guess we haven't solved that problem for PipeOpRegrAvg / PipeOpClassifAvg either.)

[pfistfl]

The number of output cols: We can just store the number of outputs in train and enforce the same length in test.
Aggregating using mean or m̀ode` might also work (perhaps this could be an option),