predict.gbm {gbm} | R Documentation |
Predicted values based on a generalized boosted model object
predict.gbm(object,newdata,n.trees, type="link", single.tree=FALSE, ...)
object |
Object of class inheriting from (gbm.object ) |
newdata |
Data frame of observations for which to make predictions |
n.trees |
Number of trees used in the prediction |
type |
The scale on which gbm makes the predictions |
single.tree |
If single.tree=TRUE then predict.gbm returns
only the predictions from tree n.trees . |
... |
further arguments passed to or from other methods |
predict.gbm
runs each observation in newdata
through the trees
described by object$trees[1:n.trees]
, the first n.trees in the boosting
sequence. The function returns sum of the predictions from each of the trees.
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.
Returns a vector of predictions. By default the predictions are on the scale of f(x). For example, for the Bernoulli loss the returned value is on the log odds scale, poisson loss on the log scale, and coxph is on the log hazard scale.
If link="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.
Greg Ridgeway gregr@rand.org