Open bdwilliamson opened 1 year ago
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!