context("mlr_resampling_subsampling")
test_that("subsampling has no duplicated ids", {
r = rsmp("subsampling")
expect_identical(r$duplicated_ids, FALSE)
})
test_that("stratification", {
data = data.table(y = rep(letters[1:2], times = c(90, 10)), x1 = runif(100), x2 = rep(LETTERS[1:2], times = c(50, 50)))
b = as_data_backend(data)
task = TaskClassif$new("stratify_data", b, target = "y")
r = rsmp("subsampling", ratio = 0.5, repeats = 3, stratify = TRUE)
r$instantiate(task)
for (i in seq_len(r$iters)) {
expect_equal(task$data(r$train_set(i))[y == "a", .N], 45)
expect_equal(task$data(r$train_set(i))[y == "b", .N], 5)
expect_equal(task$data(r$test_set(i))[y == "a", .N], 45)
expect_equal(task$data(r$test_set(i))[y == "b", .N], 5)
}
})
test_that("grouping", {
r = rsmp("subsampling", ratio = 0.5, repeats = 3)
expect_grouping_works(r)
})
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