mlr_resamplings_spcv_disc {mlr3spatiotempcv}

(sperrorest) Spatial "disc" resampling

Description

Spatial partitioning using circular test areas of one of more observations. Optionally, a buffer around the test area can be used to exclude observations. See the upstream implementation at sperrorest::partition_disc() and Brenning (2012) for further information.

Parameters

• folds (integer(1))
  Number of folds.

• radius (numeric(1))
  Radius of test area disc.

• buffer (integer(1))
  Radius around test area disc which is excluded from training or test set.

• prob (integer(1))
  Optional argument passed down to sample().

• replace (logical(1))
  Optional argument passed down to sample(). Sample with or without replacement.

Super class

mlr3::Resampling -> ResamplingSpCVDisc

Active bindings

iters

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

Methods

Public methods

• ResamplingSpCVDisc$new()

• ResamplingSpCVDisc$instantiate()

• ResamplingSpCVDisc$clone()

Inherited methods

• mlr3::Resampling$format()
• mlr3::Resampling$help()
• mlr3::Resampling$print()
• mlr3::Resampling$test_set()
• mlr3::Resampling$train_set()

Method new()

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

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

Usage

ResamplingSpCVDisc$new(id = "spcv_disc")

Arguments

id

character(1)
Identifier for the resampling strategy.

Method instantiate()

Materializes fixed training and test splits for a given task.

Usage

ResamplingSpCVDisc$instantiate(task)

Arguments

task

Task
A task to instantiate.

Method clone()

The objects of this class are cloneable with this method.

Usage

ResamplingSpCVDisc$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. doi:10.1109/igarss.2012.6352393.

Examples

library(mlr3)
task = tsk("ecuador")

# Instantiate Resampling
rcv = rsmp("spcv_disc", folds = 3L, radius = 200L, buffer = 200L)
rcv$instantiate(task)

# Individual sets:
rcv$train_set(1)
rcv$test_set(1)
# check that no obs are in both sets
intersect(rcv$train_set(1), rcv$test_set(1)) # good!

# Internal storage:
rcv$instance # table