Create train and test splits to be used in the cross_validation function

Train and test splits

Usage

create_train_test_indices(
  data,
  cv_type = c("k-fold", "loo", "lpo"),
  k = 5,
  percentage = 20,
  number_folds = 10
)

data: A list, data.frame, SpatialPointsDataFrame or metric_graph_data objects.
cv_type: The type of the folding to be carried out. The options are k-fold for k-fold cross-validation, in which case the parameter k should be provided, loo, for leave-one-out and lpo for leave-percentage-out, in this case, the parameter percentage should be given, and also the number_folds with the number of folds to be done. The default is k-fold.
k: The number of folds to be used in k-fold cross-validation. Will only be used if cv_type is k-fold.
percentage: The percentage (from 1 to 99) of the data to be used to train the model. Will only be used if cv_type is lpo.
number_folds: Number of folds to be done if cv_type is lpo.

A list with two elements, train containing the training indices and test containing indices.