Estimates the optimal number of boosting iterations for a gbm object
and optionally plots various performance measures
gbm.perf(object, plot.it = TRUE, oobag.curve = FALSE, overlay = TRUE,
method)A gbm.object created from an initial call to
gbm.
An indicator of whether or not to plot the performance
measures. Setting plot.it = TRUE creates two plots. The first plot
plots object$train.error (in black) and object$valid.error
(in red) versus the iteration number. The scale of the error measurement,
shown on the left vertical axis, depends on the distribution
argument used in the initial call to gbm.
Indicates whether to plot the out-of-bag performance measures in a second plot.
If TRUE and oobag.curve=TRUE then a right y-axis is added to the training and test error plot and the estimated cumulative improvement in the loss function is plotted versus the iteration number.
Indicate the method used to estimate the optimal number of
boosting iterations. method = "OOB" computes the out-of-bag estimate
and method = "test" uses the test (or validation) dataset to compute
an out-of-sample estimate. method = "cv" extracts the optimal number
of iterations using cross-validation if gbm was called with
cv.folds > 1.
gbm.perf Returns the estimated optimal number of iterations.
The method of computation depends on the method argument.