You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
For continuous outcomes, SL.polymars returns list(pred = pred, fit = list(object = fit.mars)), whereas for binary outcomes, SL.polymars returns list(pred = pred, fit = list(fit = fit.mars)). I think the former is used throughout the rest of SuperLearner, so it would be great to have the binary-outcome polymars behave similarly. Thanks!
The text was updated successfully, but these errors were encountered:
I believe this traces back to the different polymars predict methods, polspline::predict.polymars uses object, while polymars::ppolyclass uses fit. Let me check if there would be any adverse consequences of the change to align with object.
For continuous outcomes,
SL.polymars
returnslist(pred = pred, fit = list(object = fit.mars))
, whereas for binary outcomes,SL.polymars
returnslist(pred = pred, fit = list(fit = fit.mars))
. I think the former is used throughout the rest ofSuperLearner
, so it would be great to have the binary-outcome polymars behave similarly. Thanks!The text was updated successfully, but these errors were encountered: