crossv_mc: Generate test-training pairs for cross-validation
crossv_kfold splits the data into k exclusive partitions,
and uses each partition for a test-training split. crossv_mc
generates n random partitions, holding out test of the
data for training. crossv_loo performs leave-one-out
cross-validation, i.e., n = nrow(data) training partitions containing
n - 1 rows each.
crossv_mc(data, n, test = 0.2, id = ".id")
crossv_kfold(data, k = 5, id = ".id")
crossv_loo(data, id = ".id")
A data frame with columns test, train, and .id.
test and train are list-columns containing resample() objects.
The number of rows is n for crossv_mc(), k for crossv_kfold()
and nrow(data) for crossv_loo().
A data frame
Number of test-training pairs to generate (an integer).
Proportion of observations that should be held out for testing
Name of variable that gives each model a unique integer id.