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 = ""
)
gbm.perf
returns the estimated optimal number of iterations.
The method of computation depends on the method
argument.
a GBMFit
object created from an initial
call to gbmt
or gbm
.
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.
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.
the main title for the plot. Defaults to main =
""
.
gbmt
gbmt_performance
plot.GBMTPerformance