Nothing
test_that("LearnerClassifSpatial ignores observations with missing values", {
skip_if_not_installed("mlr3learners")
require_namespaces("mlr3learners")
# train task
stack = generate_stack(list(
numeric_layer("x_1"),
factor_layer("y", levels = c("a", "b"))),
dimension = 100)
vector = sample_stack(stack, n = 100)
task_train = as_task_classif_st(vector, id = "test_vector", target = "y")
learner = lrn("classif.ranger")
learner$train(task_train)
# predict task
stack$y = NULL
stack = mask_stack(stack)
task_predict = as_task_unsupervised(stack, id = "test")
learner_spatial = LearnerClassifSpatial$new(learner)
pred = learner_spatial$predict(task_predict)
expect_true(all(is.na(pred$response[seq(100)])))
expect_numeric(pred$response, any.missing = TRUE, all.missing = FALSE)
})
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