mlr3spatiotempcv (version 1.0.1)

ResamplingRepeatedSpCVTiles: (sperrorest) Repeated spatial "tiles" resampling

Description

(sperrorest) Repeated spatial "tiles" resampling

(sperrorest) Repeated spatial "tiles" resampling

mlr3spatiotempcv notes

The 'Description' and 'Note' fields are inherited from the respective upstream function.

For a list of available arguments, please see sperrorest::partition_tiles.

This method is similar to ResamplingSpCVBlock.

Super class

mlr3::Resampling -> ResamplingRepeatedSpCVTiles

Active bindings

iters

integer(1) Returns the number of resampling iterations, depending on the values stored in the param_set.

Methods

Public methods

• ResamplingRepeatedSpCVTiles$new()

• ResamplingRepeatedSpCVTiles$folds()

• ResamplingRepeatedSpCVTiles$repeats()

• ResamplingRepeatedSpCVTiles$instantiate()

• ResamplingRepeatedSpCVTiles$clone()

• mlr3::Resampling$format()

• mlr3::Resampling$help()

• mlr3::Resampling$print()

• mlr3::Resampling$test_set()

• mlr3::Resampling$train_set()

Method new()

Create a "Spatial 'Tiles' resampling" resampling instance.

For a list of available arguments, please see sperrorest::partition_tiles.

Usage

ResamplingRepeatedSpCVTiles$new(id = "repeated_spcv_tiles")

Arguments

id

character(1) Identifier for the resampling strategy.

Method folds()

Translates iteration numbers to fold number.

Usage

ResamplingRepeatedSpCVTiles$folds(iters)

Arguments

iters

integer() Iteration number.

Method repeats()

Translates iteration numbers to repetition number.

Usage

ResamplingRepeatedSpCVTiles$repeats(iters)

Arguments

iters

integer() Iteration number.

Method instantiate()

Materializes fixed training and test splits for a given task.

Usage

ResamplingRepeatedSpCVTiles$instantiate(task)

Arguments

task

Task A task to instantiate.

Method clone()

The objects of this class are cloneable with this method.

Usage

ResamplingRepeatedSpCVTiles$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Brenning A (2012). “Spatial cross-validation and bootstrap for the assessment of prediction rules in remote sensing: The R package sperrorest.” In 2012 IEEE International Geoscience and Remote Sensing Symposium. 10.1109/igarss.2012.6352393.

See Also

ResamplingSpCVBlock

Examples

# NOT RUN {
if (mlr3misc::require_namespaces("sperrorest", quietly = TRUE)) {
  library(mlr3)
  task = tsk("ecuador")

  # Instantiate Resampling
  rrcv = rsmp("repeated_spcv_tiles",
    repeats = 2,
    nsplit = c(4L, 3L), reassign = FALSE)
  rrcv$instantiate(task)

  # Individual sets:
  rrcv$iters
  rrcv$folds(10:12)
  rrcv$repeats(10:12)

  # Individual sets:
  rrcv$train_set(1)
  rrcv$test_set(1)
  intersect(rrcv$train_set(1), rrcv$test_set(1))

  # Internal storage:
  rrcv$instance # table
}
# }