mdl_xgboost: Wrapper for 'xgboost::xgboost()'.

In ddml: Double/Debiased Machine Learning

Wrapper for xgboost::xgboost().

Description

Simple wrapper for xgboost::xgboost() with some changes to the default arguments.

Usage

mdl_xgboost(y, X, nrounds = 500, verbose = 0, ...)

Arguments

y	The outcome variable.
X	The (sparse) feature matrix.
nrounds	max number of boosting iterations.
verbose	If 0, xgboost will stay silent. If 1, it will print information about performance. If 2, some additional information will be printed out. Note that setting verbose > 0 automatically engages the cb.print.evaluation(period=1) callback function.
...	Additional arguments passed to xgboost. See xgboost::xgboost() for a complete list of arguments.

Value

mdl_xgboost returns an object of S3 class mdl_xgboost as a simple mask to the return object of xgboost::xgboost().

References

Chen T, Guestrin C (2011). "Xgboost: A Scalable Tree Boosting System." Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 785–794.

See Also

xgboost::xgboost()

Other ml_wrapper: mdl_glmnet(), mdl_glm(), mdl_ranger(), ols()

Examples

xgboost_fit <- mdl_xgboost(rnorm(50), matrix(rnorm(150), 50, 3),
                           nrounds = 1)
class(xgboost_fit)

ddml documentation built on Oct. 3, 2024, 1:13 a.m.