R/getHyperPars.R

In mlr: Machine Learning in R

#' @title Get current parameter settings for a learner.
#'
#' @description Retrieves the current hyperparameter settings of a learner.
#'
#' @details This function only shows hyperparameters that differ from the
#' learner default (because `mlr` changed the default) or if the user set
#' hyperparameters manually during learner creation. If you want to have an
#' overview of all available hyperparameters use [getParamSet()].
#'
#' @param learner ([Learner])\cr The learner.
#' @param for.fun (`character(1)`)\cr Restrict the returned settings to
#'   hyperparameters corresponding to `when` the are used (see
#'   [ParamHelpers::LearnerParam]). Must be a subset of: \dQuote{train},
#'   \dQuote{predict} or \dQuote{both}. Default is `c("train", "predict",
#'   "both")`.
#' @return ([list]). A named list of values.
#' @family learner
#' @export
#' @examples
#' getHyperPars(makeLearner("classif.ranger"))
#'
#' ## set learner hyperparameter `mtry` manually
#' getHyperPars(makeLearner("classif.ranger", mtry = 100))
getHyperPars = function(learner, for.fun = c("train", "predict", "both")) {
  assertSubset(for.fun, choices = c("train", "predict", "both"))
  UseMethod("getHyperPars")
}

#' @export
getHyperPars.Learner = function(learner, for.fun = c("train", "predict", "both")) {
  assertClass(learner, classes = "Learner")
  pars = learner$par.set$pars
  pv = learner$par.vals
  ns = Filter(function(x) pars[[x]]$when %in% for.fun, names(pv))
  pv[ns]
}

getHyperParsString = function(learner, show.missing.values = TRUE) {
  # FIXME
  # filter methods in the param set let `paramValueToString` fail.
  # Delete them for the printer to work
  if ("fw.base.methods" %in% names(learner$par.set$pars)) {
    learner$par.set$pars$fw.base.methods = NULL
    learner$par.set$pars$fw.method = NULL
    learner$par.vals$fw.method = NULL
    learner$par.vals$fw.base.methods = NULL
  }
  if ("fw.base.methods" %in% names(learner$next.learner$par.set$pars)) {
    learner$next.learner$par.set$pars$fw.base.methods = NULL
    learner$next.learner$par.set$pars$fw.method = NULL
    learner$next.learner$par.vals$fw.method = NULL
    learner$next.learner$par.vals$fw.base.methods = NULL
  }
  hps = getHyperPars(learner)
  ns = names(hps)
  pars = getParamSet(learner)$pars[ns]
  s = mapply(paramValueToString, pars, hps, MoreArgs = list(show.missing.values = show.missing.values))
  stri_paste(ns, s, sep = "=", collapse = ",")
}