gbm.perf: GBM performance
In gbm: Generalized Boosted Regression Models

gbm.perf

R Documentation

GBM performance

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)

`object`	A `gbm.object` created from an initial call to `gbm`.
`plot.it`	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`.
`oobag.curve`	Indicates whether to plot the out-of-bag performance measures in a second plot.
`overlay`	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.
`method`	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.