Generic S3 plot() and autoplot() (ggplot2) methods.

# S3 method for ResamplingCustomCV
autoplot(
  object,
  task,
  fold_id = NULL,
  plot_as_grid = TRUE,
  train_color = "#0072B5",
  test_color = "#E18727",
  ...
)

# S3 method for ResamplingCustomCV
plot(x, ...)

Arguments

object

[Resampling]
mlr3 spatial resampling object of class ResamplingCustomCV.

task

[TaskClassifST]/[TaskRegrST]
mlr3 task object.

fold_id

[numeric]
Fold IDs to plot.

plot_as_grid

[logical(1)]
Should a gridded plot using via patchwork be created? If FALSE a list with of ggplot2 objects is returned. Only applies if a numeric vector is passed to argument fold_id.

train_color

[character(1)]
The color to use for the training set observations.

test_color

[character(1)]
The color to use for the test set observations.

...

Passed to geom_sf(). Helpful for adjusting point sizes and shapes.

x

[Resampling]
mlr3 spatial resampling object of class ResamplingCustomCV.

See also

Examples

if (mlr3misc::require_namespaces(c("sf", "patchwork"), quietly = TRUE)) { library(mlr3) library(mlr3spatiotempcv) task = tsk("ecuador") breaks = quantile(task$data()$dem, seq(0, 1, length = 6)) zclass = cut(task$data()$dem, breaks, include.lowest = TRUE) resampling = rsmp("custom_cv") resampling$instantiate(task, f = zclass) autoplot(resampling, task) + ggplot2::scale_x_continuous(breaks = seq(-79.085, -79.055, 0.01)) autoplot(resampling, task, fold_id = 1) autoplot(resampling, task, fold_id = c(1, 2)) * ggplot2::scale_x_continuous(breaks = seq(-79.085, -79.055, 0.01)) }