Open jarauh opened 3 years ago
Thanks for your suggestion!
I'm not a big fan, for a few reasons:
Unless you have a strong argument in favor of this proposal, I'd close it as a wontfix.
Thanks for your quick answer.
roc.lm
would cover most cases (at least those cases that try to be consistent with "lm", such as "glm" and "gam"). Basically, you only need to extract/generate predictions and outcomes. I'm not sure about the outcomes, but most models have a predict method that could be called, so things should be rather straight-forward.
It would be nice if there would be roc/auc-methods for objects of class
lm
.The methods could have signature:
The function should run
predict(model, newdata = newdata, ...)
to obtain predictions, extract the observed outcome from either newdata or the model and then compute the roc or auc.