Check a plan's folds are well formed, and describe them.

Run this before any training: a broken plan caught here costs a second, caught later it costs the whole run. Checks that, within each fold, train and validation are disjoint; that test (when present) appears in neither; and that across the folds every pooled row is validated exactly once – the property that makes the k metrics a partition of the pool rather than an arbitrary set of overlapping subsets.

Usage

check_fold_plan(plan, meta = NULL, group = "auto")

Arguments

plan: A fold_plan.
meta: The point table the plan was made for. Given, the grouping is proven against it: no group may be split across train and validation.
group: How the rows group, as in holdout().

Value

tibble, one row per fold.

Examples

ex <- example_landscape()
meta <- data.frame(sample_id = seq_len(nrow(ex$profiles)), x = ex$profiles$x,
                   y = ex$profiles$y)
plan <- spatial_folds(meta, k = 3, test_frac = 0.2, block_size = 0.05)
check_fold_plan(plan, meta)
#> # A tibble: 3 × 4
#>    fold n_train n_validation n_test
#>   <int>   <int>        <int>  <int>
#> 1     1      78           37     45
#> 2     2      76           39     45
#> 3     3      76           39     45