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Update 12-spatial-cv.Rmd
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12-spatial-cv.Rmd

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