This functionality was planned... but was not implemented from what I can tell.
It seems like a good safety guard. It is also important for those algorithms that rely on a test-time fitting (it would make sure that a dedicated API used for this avoiding any confusion).
The only question that might be slightly annoying: what if we fit the pipeline from a single source/single target but with non-default domain labels, like say {-5, 7}, when running predict w/o sample_domain input this will fail (because we assume predict inputs to be targets with a default label). I guess it's okay, in a way you created the problem for yourself. To be sure that what you put into predict is correct, it has to have domain labels attached to it.
This functionality was planned... but was not implemented from what I can tell.
It seems like a good safety guard. It is also important for those algorithms that rely on a test-time fitting (it would make sure that a dedicated API used for this avoiding any confusion).
The only question that might be slightly annoying: what if we fit the pipeline from a single source/single target but with non-default domain labels, like say
{-5, 7}, when runningpredictw/osample_domaininput this will fail (because we assume predict inputs to be targets with a default label). I guess it's okay, in a way you created the problem for yourself. To be sure that what you put intopredictis correct, it has to have domain labels attached to it.