Scikit-learn - Cross validates score and predictions at one go?
If you run cross_val_predict then you can check the metric on the result. It is not a waste of compute time because cross_val_predict doesn't compute scores itself. 
This won't give you per-fold scores though, only the aggregated score (which is not necessarily bad). I think you can workaround that by creating KFold / ... instance explicitly and then using it to split the cross_val_predict result.
I'm not sure whether I'm missing something really easy but I have a hard time trying to google something out.
I can see there are cross_val_score and cross_val_predict functions in scikit-learn. However, I can't find a way to get both score and predictions at one go. Seems quite obvious as calling the functions above one after another is a waste of computing time. Is there a cross_val_score_predict function or similar?