Merge PR #1159: Update 12-spatial-cv.Rmd

Add note that mlr3proba is required for list_mlr3learners().
Improve code formatting for readability.

Co-Authored-By: Robin Lovelace <robinlovelace@gmail.com>
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Author: 3 people

12-spatial-cv.Rmd

@@ -325,13 +325,15 @@ mlr3viz::autoplot(task, type = "pairs")
 
 Having created a task, we need to choose a **learner** that determines the statistical learning\index{statistical learning} method to use.
 All classification\index{classification} **learners** start with `classif.` and all regression\index{regression} learners with `regr.` (see `?Learner` for details).
-`mlr3extralearners::list_mlr3learners()` lists all available learners and from which package **mlr3** imports them (Table \@ref(tab:lrns)).
+`mlr3extralearners::list_mlr3learners()`, which requires **mlr3proba** to be installed, lists all available learners and from which package **mlr3** imports them (Table \@ref(tab:lrns)).
 To find out about learners that are able to model a binary response variable, we can run:
 
 ```{r 12-spatial-cv-12, eval=FALSE}
+install.packages("mlr3proba", repos = "https://mlr-org.r-universe.dev")
 mlr3extralearners::list_mlr3learners(
   filter = list(class = "classif", properties = "twoclass"),
-  select = c("id", "mlr3_package", "required_packages")) |>
+  select = c("id", "mlr3_package", "required_packages")
+) |>
   head()
 ```