man-roxygen/impute_doc_intro.R

In mlr-org/mlrCPO: Composable Preprocessing Operators and Pipelines for Machine Learning

#' @template cpo_doc_intro
#' @description
#' Allows imputation of missing feature values through various techniques.
#' Note that you have the possibility to re-impute a data set
#' in the same way as the imputation was performed during training.
#' This especially comes in handy during resampling when one wants to perform the
#' same imputation on the test set as on the training set.
#'
#' @details
#' The description object contains these slots
#' \describe{
#'   \item{target [\code{character}]}{See argument.}
#'   \item{features [\code{character}]}{Feature names (column names of \code{data}).},
#'   \item{classes [\code{character}]}{Feature classes (storage type of \code{data}).}
#'   \item{lvls [\code{named list}]}{Mapping of column names of factor features to their levels,
#'     including newly created ones during imputation.}
#'   \item{impute [\code{named list}]}{Mapping of column names to imputation functions.}
#'   \item{dummies [\code{named list}]}{Mapping of column names to imputation functions.}
#'   \item{impute.new.levels [\code{logical(1)}]}{See argument.}
#'   \item{recode.factor.levels [\code{logical(1)}]}{See argument.}
#' }