mlr_resamplings_spcv_env function

(blockCV) "Environmental blocking" resampling

(blockCV) "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.

Examples

if (mlr3misc::require_namespaces(c("sf", "blockCV"), quietly = TRUE)) { library(mlr3) task = tsk("ecuador") # Instantiate Resampling rcv = rsmp("spcv_env", folds = 4) 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 }

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 -> ResamplingSpCVEnv

Active bindings

  • iters: integer(1)

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

Methods

Public methods

Method new()

Create an "Environmental Block" resampling instance.

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

Usage

ResamplingSpCVEnv$new(id = "spcv_env")

Arguments

  • id: character(1)

     Identifier for the resampling strategy.
    

Method instantiate()

Materializes fixed training and test splits for a given task.

Usage

ResamplingSpCVEnv$instantiate(task)

Arguments

  • task: mlr3::Task

     A task to instantiate.
    

Method clone()

The objects of this class are cloneable with this method.

Usage

ResamplingSpCVEnv$clone(deep = FALSE)

Arguments

  • deep: Whether to make a deep clone.