Spatial Buffer Cross validation implemented by the blockCV package.

## Note

However, the default settings allow to conduct a leave-one-out cross validation for two-class, multi-class and continuous response data, where each observation is one test set. For each test, all observations outside the buffer around the test observation are included in the training set.

#### Arguments

id

character(1)
Identifier for the resampling strategy.

### Method instantiate()

Materializes fixed training and test splits for a given task.

#### Arguments

deep

Whether to make a deep clone.

## Examples

if (mlr3misc::require_namespaces(c("sf", "blockCV"), quietly = TRUE)) {
library(mlr3)
rcv$instantiate(task) # Individual sets: rcv$train_set(1)
rcv$test_set(1) intersect(rcv$train_set(1), rcv$test_set(1)) # Internal storage: # rcv$instance
#> integer(0)