ResamplingSpCVDisc: (sperrorest) Spatial "disc" resampling

Description mlr3spatiotempcv notes Super class Active bindings Methods Note References See Also Examples

Description

partition_disc partitions the sample into training and tests set by selecting circular test areas (possibly surrounded by an exclusion buffer) and using the remaining samples as training samples (leave-one-disc-out cross-validation). partition_loo creates training and test sets for leave-one-out cross-validation with (optional) buffer.

mlr3spatiotempcv notes

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

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

This method is similar to ResamplingSpCVBuffer.

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

Inherited methods

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.

Note

Test area discs are centered at (random) samples, not at general random locations. Test area discs may (and likely will) overlap independently of the value of replace. replace only controls the replacement of the center point of discs when drawing center points from the samples.

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.

See Also

ResamplingSpCVBuffer

Examples

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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

mlr-org/mlr3spatiotempcv documentation built on May 4, 2021, 9:44 a.m.