| gbm.object | R Documentation | 
These are objects representing fitted gbms.
initF | 
 The "intercept" term, the initial predicted value to which trees make adjustments.  | 
fit | 
 A vector containing the fitted values on the scale of regression function (e.g. log-odds scale for bernoulli, log scale for poisson).  | 
train.error | 
 A vector of length equal to the number of fitted trees containing the value of the loss function for each boosting iteration evaluated on the training data.  | 
valid.error | 
 A vector of length equal to the number of fitted trees containing the value of the loss function for each boosting iteration evaluated on the validation data.  | 
cv.error | 
 If   | 
oobag.improve | 
 A vector of
length equal to the number of fitted trees containing an out-of-bag estimate
of the marginal reduction in the expected value of the loss function. The
out-of-bag estimate uses only the training data and is useful for estimating
the optimal number of boosting iterations. See   | 
trees | 
 A list containing the tree structures. The components are best
viewed using   | 
c.splits | 
 A list of all
the categorical splits in the collection of trees. If the   | 
cv.fitted | 
 If cross-validation was performed, the cross-validation predicted values on the scale of the linear predictor. That is, the fitted values from the i-th CV-fold, for the model having been trained on the data in all other folds.  | 
The following components must be included in a
legitimate gbm object.
Greg Ridgeway gregridgeway@gmail.com
gbm
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