mlr_resamplings_repeated_spcv_env function

(blockCV) Repeated "environmental blocking" resampling

Splits data by clustering in the feature space. See the upstream implementation at blockCV::cv_cluster() and Valavi et al. (2018) for further information.

Details

Useful when the dataset is supposed to be split on environmental information which is present in features. The method allows for a combination of multiple features for clustering.

The input of raster images directly as in blockCV::cv_cluster() is not supported. See list("mlr3spatial") and its raster DataBackends for such support in list("mlr3").

Parameters

• folds (integer(1))

  Number of folds.

• features (character())

  The features to use for clustering.

• repeats (integer(1))

  Number of repeats.

Examples

if (mlr3misc::require_namespaces(c("sf", "blockCV"), quietly = TRUE)) {
  library(mlr3)
  task = tsk("ecuador")

  # Instantiate Resampling
  rrcv = rsmp("repeated_spcv_env", folds = 4, repeats = 2)
  rrcv$instantiate(task)

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

  # Internal storage:
  rrcv$instance
}

References

Valavi R, Elith J, Lahoz-Monfort JJ, Guillera-Arroita G (2018). blockCV: an R package for generating spatially or environmentallyseparated folds for k-fold cross-validation of species distributionmodels.

bioRxiv. tools:::Rd_expr_doi("10.1101/357798") .

Super class

mlr3::Resampling -> ResamplingRepeatedSpCVEnv

Active bindings

• iters: integer(1)

   Returns the number of resampling iterations, depending on the values stored in the `param_set`.
  

Methods

Public methods

• list("ResamplingRepeatedSpCVEnv$new()")

• list("ResamplingRepeatedSpCVEnv$folds()")

• list("ResamplingRepeatedSpCVEnv$repeats()")

• list("ResamplingRepeatedSpCVEnv$instantiate()")

• list("ResamplingRepeatedSpCVEnv$clone()")

Method new()

Create an "Environmental Block" repeated resampling instance.

For a list of available arguments, please see blockCV::cv_cluster .

Usage

ResamplingRepeatedSpCVEnv$new(id = "repeated_spcv_env")

Arguments

• id: character(1)

   Identifier for the resampling strategy.
  

Method folds()

Translates iteration numbers to fold number.

Usage

ResamplingRepeatedSpCVEnv$folds(iters)

Arguments

• iters: integer()

   Iteration number.
  

Method repeats()

Translates iteration numbers to repetition number.

Usage

ResamplingRepeatedSpCVEnv$repeats(iters)

Arguments

• iters: integer()

   Iteration number.
  

Method instantiate()

Materializes fixed training and test splits for a given task.

Usage

ResamplingRepeatedSpCVEnv$instantiate(task)

Arguments

• task: mlr3::Task

   A task to instantiate.
  

Method clone()

The objects of this class are cloneable with this method.

Usage

ResamplingRepeatedSpCVEnv$clone(deep = FALSE)

Arguments

• deep: Whether to make a deep clone.