mlr3spatiotempcv (version 1.0.1)

ResamplingRepeatedSptCVCstf: (CAST) Repeated "leave-location-and-time-out" resampling

Description

(CAST) Repeated "leave-location-and-time-out" resampling

(CAST) Repeated "leave-location-and-time-out" resampling

mlr3spatiotempcv notes

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

For a list of available arguments, please see CAST::CreateSpacetimeFolds.

Super class

mlr3::Resampling -> ResamplingRepeatedSptCVCstf

Active bindings

iters

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

Methods

Public methods

• ResamplingRepeatedSptCVCstf$new()

• ResamplingRepeatedSptCVCstf$folds()

• ResamplingRepeatedSptCVCstf$repeats()

• ResamplingRepeatedSptCVCstf$instantiate()

• ResamplingRepeatedSptCVCstf$clone()

• mlr3::Resampling$format()

• mlr3::Resampling$help()

• mlr3::Resampling$print()

• mlr3::Resampling$test_set()

• mlr3::Resampling$train_set()

Method new()

Create a "Spacetime Folds" resampling instance.

For a list of available arguments, please see CAST::CreateSpacetimeFolds.

Usage

ResamplingRepeatedSptCVCstf$new(id = "repeated_sptcv_cstf")

Arguments

id

character(1) Identifier for the resampling strategy.

Method folds()

Translates iteration numbers to fold number.

Usage

ResamplingRepeatedSptCVCstf$folds(iters)

Arguments

iters

integer() Iteration number.

Method repeats()

Translates iteration numbers to repetition number.

Usage

ResamplingRepeatedSptCVCstf$repeats(iters)

Arguments

iters

integer() Iteration number.

Method instantiate()

Materializes fixed training and test splits for a given task.

Usage

ResamplingRepeatedSptCVCstf$instantiate(task)

Arguments

task

Task A task to instantiate.

Method clone()

The objects of this class are cloneable with this method.

Usage

ResamplingRepeatedSptCVCstf$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

Zhao Y, Karypis G (2002). “Evaluation of Hierarchical Clustering Algorithms for Document Datasets.” 11th Conference of Information and Knowledge Management (CIKM), 51-524. http://glaros.dtc.umn.edu/gkhome/node/167.

Examples

# NOT RUN {
library(mlr3)
library(mlr3spatiotempcv)
task = tsk("cookfarm")

# Instantiate Resampling
rrcv = rsmp("repeated_sptcv_cstf", folds = 3, repeats = 5, time_var = "Date")
rrcv$instantiate(task)
# Individual sets:
rrcv$iters
rrcv$folds(1:6)
rrcv$repeats(1:6)

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

# Internal storage:
rrcv$instance # table
# }