gbm.perf: GBMT Performance
In gbm-developers/gbm3: Generalized Boosted Regression Models

gbm.perf

R Documentation

GBMT Performance

Estimates optimal number of boosting iterations given a GBMFit object and optionally plots various performance measures.

gbm.perf(
  object,
  plot.it = TRUE,
  oobag.curve = FALSE,
  overlay = TRUE,
  method,
  main = ""
)

`object`	a `GBMFit` object created from an initial call to `gbmt` or `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 the train error (in black) and the validation 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.
`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.
`main`	the main title for the plot. Defaults to `main = ""`.

gbm.perf returns the estimated optimal number of iterations. The method of computation depends on the method argument.