Closed BruceChen2017 closed 4 years ago
yes, it is OLS (but it can also do a ridge-penalized fit)
this function sets up the design matrix for bols
learners:
https://github.com/boost-R/mboost/blob/84712fcb27511f45ae6664078dd772d1750c8549/R/bl.R#L92
the loss
-argument defines the loss function -- as the manual says "an optional loss function with arguments y and f."
y are the responses, f is the additive predictor/model prediction
@fabian-s Thanks. What does "optional" means? If I understand correctly, such loss function would be used to calculate AIC
.Such understanding comes after I read this paper Boosting Algorithms:Regularization,Prediction and Model Fitting
there's a misunderstanding -- this forum is for reporting bugs or feature requests for mboost, not for teaching people about boosting. better forums for that kind of question: crossvalidated or any of the subreddits devoted to stats or machine learning. good luck!
Just for confirmation.If it is, which part of source code reveales this?By the way, what is the usage of
loss
agrument inFamily
object. Thanks in advance!