#' @title Hyperparameter Tuning with Successive Halving
#'
#' @include OptimizerBatchSuccessiveHalving.R
#' @name mlr_tuners_successive_halving
#' @templateVar id successive_halving
#'
#' @inherit mlr_optimizers_successive_halving description
#' @inheritSection mlr_optimizers_successive_halving Resources
#' @template section_dictionary_tuners
#' @inheritSection mlr_optimizers_successive_halving Parameters
#' @inheritSection mlr_optimizers_successive_halving Archive
#' @template section_subsample_budget
#' @template section_custom_sampler
#' @template section_progress_bars
#'
#' @section Parallelization:
#' The hyperparameter configurations of one stage are evaluated in parallel with the \CRANpkg{future} package.
#' To select a parallel backend, use the `plan()` function of the \CRANpkg{future} package.
#'
#' @template section_logging
#'
#' @source
#' `r format_bib("jamieson_2016")`
#'
#' @export
#' @template example_tuner
TunerBatchSuccessiveHalving = R6Class("TunerBatchSuccessiveHalving",
inherit = TunerBatchFromOptimizerBatch,
public = list(
#' @description
#' Creates a new instance of this [R6][R6::R6Class] class.
initialize = function() {
super$initialize(
optimizer = OptimizerBatchSuccessiveHalving$new(),
man = "mlr3hyperband::mlr_tuners_hyperband"
)
}
)
)
#' @include aaa.R
tuners[["successive_halving"]] = TunerBatchSuccessiveHalving
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