Invalid target data check: recommended action should be to drop rows with nans

Looks like the default action right now is "impute" for regression
https://github.com/alteryx/evalml/blob/main/evalml/data_checks/invalid_target_data_check.py#L247

I think a) one of the actions should be to drop rows with missing target values and b) this should be the recommended action.

Why: imputing the target is cool and can apply interesting modeling pressure in some cases. But rewriting the target is also dangerous!