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#' @title Downsample (subsample) a task or a data.frame.
#'
#' @description
#' Decrease the observations in a `task` or a `ResampleInstance`
#' to a given percentage of observations.
#'
#' @param obj ([Task] | [ResampleInstance])\cr
#' Input data or a `ResampleInstance`.
#' @param perc (`numeric(1)`)\cr
#' Percentage from (0, 1).
#' Default is 1.
#' @param stratify (`logical(1)`)\cr
#' Only for classification:
#' Should the downsampled data be stratified according to the target classes?
#' Default is `FALSE`.
#' @seealso [makeResampleInstance]
#' @return ([data.frame` | [Task] | [ResampleInstance]). Same type as `obj`.
#' @family downsample
#' @export
downsample = function(obj, perc = 1, stratify = FALSE) {
assertNumber(perc, lower = 0, upper = 1)
assertFlag(stratify)
UseMethod("downsample")
}
#' @export
downsample.Task = function(obj, perc = 1, stratify = FALSE) {
rin = makeResampleInstance("Holdout", stratify = stratify, split = perc, task = obj)
subsetTask(task = obj, subset = rin$train.inds[[1L]])
}
#' @export
downsample.ResampleInstance = function(obj, perc = 1, stratify = FALSE) {
if (stratify) {
stop("Stratifying is not supported for a ResampleInstance!")
}
obj$train.inds = lapply(obj$train.inds, function(x) sample(x, size = length(x) * perc))
return(obj)
}
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