#' Learner with Covariate Subsetting
#'
#' This learner provides fitting procedures for subsetting covariates. It is a
#' convenience utility for reducing the number of covariates to be fit.
#'
#' @docType class
#'
#' @importFrom R6 R6Class
#'
#' @export
#'
#' @keywords data
#'
#' @return Learner object with methods for training and prediction. See
#' \code{\link{Lrnr_base}} for documentation on learners.
#'
#' @format \code{\link{R6Class}} object.
#'
#' @family Learners
#'
#' @section Parameters:
#' \describe{
#' \item{\code{...}}{Not currently used.}
#' }
#'
#' @template common_parameters
#
Lrnr_subset_covariates <- R6Class(
classname = "Lrnr_subset_covariates",
inherit = Lrnr_base, portable = TRUE,
class = TRUE,
public = list(
initialize = function(...) {
params <- list(...)
super$initialize(...)
}
),
private = list(
.train = function(task) {
fit_object <- list()
return(fit_object)
},
.predict = function(task = NULL) {
# nothing to do here: we're relying on Lrnr_base to subset covariates
return(task$X)
},
.chain = function(task = NULL) {
# nothing to do here: we're relying on Lrnr_base to subset covariates
return(task)
}
)
)
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