Sort of like skipping in recipes, can we put a flag in adjust_predictions_custom() to apply it to new data (i.e. not during the model optimization/evaluation cycle)?
I'd like people to avoid exponentiating predictions prior to metric computations. We could add a similar flag to fit.tailor() that says, "We are in pure new sample prediction mode." We can set that appropriately in tune.
Sort of like skipping in recipes, can we put a flag in
adjust_predictions_custom()
to apply it to new data (i.e. not during the model optimization/evaluation cycle)?I'd like people to avoid exponentiating predictions prior to metric computations. We could add a similar flag to
fit.tailor()
that says, "We are in pure new sample prediction mode." We can set that appropriately in tune.