Make groupings for grouped rsplits — make

This function powers grouped resampling by splitting the data based upon a grouping variable and returning the assessment set indices for each split.

Usage

make_groups(
  data,
  group,
  v,
  balance = c("groups", "observations", "prop"),
  strata = NULL,
  ...
)

Arguments

data: A data frame.
group: A variable in data (single character or name) used for grouping observations with the same value to either the analysis or assessment set within a fold.
v: The number of partitions of the data set.
balance: If v is less than the number of unique groups, how should groups be combined into folds? Should be one of "groups", "observations", "prop".
strata: A variable in data (single character or name) used to conduct stratified sampling. When not NULL, each resample is created within the stratification variable. Numeric strata are binned into quartiles.
...: Arguments passed to balance functions.

Details

Not all balance options are accepted – or make sense – for all resampling functions. For instance, balance = "prop" assigns groups to folds at random, meaning that any given observation is not guaranteed to be in one (and only one) assessment set. That means balance = "prop" can't be used with group_vfold_cv(), and so isn't an option available for that function.

Similarly, group_mc_cv() and its derivatives don't assign data to one (and only one) assessment set, but rather allow each observation to be in an assessment set zero-or-more times. As a result, those functions don't have a balance argument, and under the hood always specify balance = "prop" when they call make_groups().