Estimates the optimal number of boosting iterations for a
and optionally plots various performance measures
gbm.perf(object, plot.it = TRUE, oobag.curve = FALSE, overlay = TRUE, method)
An indicator of whether or not to plot the performance measures. Setting
plot.it = TRUEcreates 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
distributionargument used in the initial call to
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
gbmwas called with
gbm.perf Returns the estimated optimal number of iterations.
The method of computation depends on the