# Does the 'fit' attribute of a gbm object contain the OOB estimates?

I have looked at the help (?gbm) and documentation for gbm.object, it only says that

fit: a vector containing the fitted values on the scale of regression function (e.g. log-odds scale for bernoulli, log scale for poisson)

Is it the OOB estimates like randomForest? That would seem unlikely to me since best_iter is not supplied to get it unless gbm has secretly decided which test I prefer.

Is there an efficient way to get the OOB estimates at all since I've already ran 5-fold cv to get best_iter?

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gbm.object looks like a variable name with an attribute called fit. –  Macro Jul 2 '12 at 12:53
Hi Macro, sorry for not being clear, gbm.object is a fitted gbm. yes, one of the attribute is fit, and I want to know if it is OOB. –  King Jul 2 '12 at 13:03
I don't think you're going to find what you're looking for. First of all, there is no real concept of "OOB Predictions" for a full gbm fit. It does save the OOB decrease (or increase) in error after each tree, but that does not equate to an OOB prediction. Since the trees are in sequence (boosted) instead of in parallel (bagged) there is no way to get "untainted" predictions for the training data.