boost_control {mboost} | R Documentation |
Definition of the initial number of boosting iterations, step size and other hyper-parameters for boosting algorithms.
boost_control(mstop = 100, nu = 0.1, constraint = FALSE, risk = c("inbag", "oobag", "none"), savedata = TRUE, center = FALSE, trace = FALSE, save_ensembless=TRUE)
mstop |
an integer giving the number of initial boosting iterations. |
nu |
a double (between 0 and 1) defining the step size or shrinkage parameter. |
constraint |
a logical indicating whether the working responses should be restricted to (-1, +1). |
risk |
a character indicating how the empirical risk should be
computed for each boosting iteration. inbag leads to
risks computed for the learning sample (i.e., all non-zero weights),
oobag to risks based on the out-of-bag (all observations with
zero weights) and none to no risk computations at all. |
savedata |
a logical, should the data be saved in the returned object? |
center |
a logical indicating if the numerical covariates should be mean
centered before fitting. Only implemented for
glmboost . In gamboost and
blackboost centering is not needed. |
trace |
a logical triggering printout of status information during the fitting process. |
save_ensembless |
a logical indicating if the list of baselearners should be saved and returned. This list is generally needed but can be suppressed to reduce memory usage (not recommended). |
Objects returned by this function specify hyper-parameters of the
boosting algorithms implemented in glmboost
,
gamboost
and blackboost
(via the control
argument).
An object of class boost_control
, a list.