Estimates the optimal number of boosting iterations for a TDboost object and
optionally plots various performance measures
TDboost.perf(object,
plot.it = TRUE,
oobag.curve = FALSE,
overlay = TRUE,
method)TDboost.perf returns the estimated optimal number of iterations. The method
of computation depends on the method argument.
a TDboost.object created from an initial call to
TDboost.
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 TDboost.
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 TDboost was called
with cv.folds>1
Yi Yang yi.yang6@mcgill.ca, Wei Qian wxqsma@rit.edu and Hui Zou hzou@stat.umn.edu
Yang, Y., Qian, W. and Zou, H. (2013), “A Boosted Tweedie Compound Poisson Model for Insurance Premium” Preprint.
G. Ridgeway (1999). “The state of boosting,” Computing Science and Statistics 31:172-181.
G. Ridgeway (2003). "A note on out-of-bag estimation for estimating the optimal number of boosting iterations," Working paper.
TDboost, TDboost.object