R: GBM performance

gbm.perf {gbm} | R Documentation

## GBM performance

### Description

Estimates the optimal number of boosting iterations for a `gbm` object and optionally plots various performance measures

### Usage

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

### Arguments

`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

### Value

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

### Author(s)

Greg Ridgeway gregridgeway@gmail.com

### See Also

`gbm`, `gbm.object`

[Package gbm version 2.1.3 Index]