"predict"(object, newdata, n.trees, type="link", single.tree=FALSE, ...)
gbm.object
) n.trees
may
be a vector in which case predictions are returned for each
iteration specifiedsingle.tree=TRUE
then predict.gbm
returns
only the predictions from tree(s) n.trees
type="response"
then gbm
converts back to the same scale as the outcome. Currently the only effect this will have is returning probabilities for bernoulli and expected counts for poisson. For the other distributions "response" and "link" return the same.
predict.gbm
produces predicted values for each observation in newdata
using the the first n.trees
iterations of the boosting sequence. If n.trees
is a vector than the result is a matrix with each column representing the predictions from gbm models with n.trees[1]
iterations, n.trees[2]
iterations, and so on.The predictions from gbm
do not include the offset term. The user may add the value of the offset to the predicted value if desired.
If object
was fit using gbm.fit
there will be no
Terms
component. Therefore, the user has greater responsibility to make
sure that newdata
is of the same format (order and number of variables)
as the one originally used to fit the model.
gbm
, gbm.object