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[R] update predict docs (#8886)

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Krzysztof Dyba 2023-03-08 22:58:39 +01:00 committed by GitHub
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4
R-package/R/xgb.Booster.R
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@ -214,6 +214,10 @@ xgb.Booster.complete <- function(object, saveraw = TRUE) {
#' Since it quadratically depends on the number of features, it is recommended to perform selection
#' of the most important features first. See below about the format of the returned results.
#'
#' The \code{predict()} method uses as many threads as defined in \code{xgb.Booster} object (all by default).
#' If you want to change their number, then assign a new number to \code{nthread} using \code{\link{xgb.parameters<-}}.
#' Note also that converting a matrix to \code{\link{xgb.DMatrix}} uses multiple threads too.
#'
#' @return
#' The return type is different depending whether \code{strict_shape} is set to \code{TRUE}. By default,
#' for regression or binary classification, it returns a vector of length \code{nrows(newdata)}.

4
R-package/man/predict.xgb.Booster.Rd
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@ -122,6 +122,10 @@ With \code{predinteraction = TRUE}, SHAP values of contributions of interaction
are computed. Note that this operation might be rather expensive in terms of compute and memory.
Since it quadratically depends on the number of features, it is recommended to perform selection
of the most important features first. See below about the format of the returned results.
The \code{predict()} method uses as many threads as defined in \code{xgb.Booster} object (all by default).
If you want to change their number, then assign a new number to \code{nthread} using \code{\link{xgb.parameters<-}}.
Note also that converting a matrix to \code{\link{xgb.DMatrix}} uses multiple threads too.
}
\examples{
## binary classification: