Internal function to get the learners — get_learners

The following learners "classif.h2o.glm", "classif.lda", "classif.mda", "classif.naiveBayes", "classif.IBk", "classif.kknn", "classif.featureless" do not get transformed into a TuneWrapper. The following learners c("classif.h2o.gbm", "classif.h2o.deeplearning", "classif.nnTrain", "classif.xgboost") are tuned with mlr::makeTuneControlRandom(). All other learners are tuned with mlr::makeTuneControlGrid(). Setting the possible hyper-parameters values is handled by get_ps()

get_learners_internal(
  lrn_ids,
  data,
  inner_resampling,
  grid_resolution,
  .info = FALSE,
  pca = FALSE,
  corr = FALSE,
  prob = TRUE,
  randomit = 100,
  mes
)

Arguments

lrn_ids	`character`, list of `mlr` learner idenfitiers
data	a named list with two elements `data` and `labels`
inner_resampling	`resampleDesc` from `mlr`, the inner folds of the nested resampling
grid_resolution	`numeric`, defines the granularity of the discrete tuning grid
.info	`logical`, controls the amount of information printed when tuning
pca	`logical`, is a PCA performed
corr	`logical`, are highly correlated predictors removed
prob	`logical`, controls the type of output, if `TRUE` probabilities, if `FALSE` response
randomit	`numeric`, the number of iteration for the random discrete tuning
mes	`mlr` list of measure to compute while tuning, the learner are tuning against the first element

Value

a list of mlr learners