Nothing
test_that("recipe leakage validator flags trained recipes", {
skip_if_not_installed("recipes")
df <- data.frame(
outcome = factor(rep(c(0, 1), each = 5), levels = c(0, 1)),
x1 = rnorm(10),
x2 = rnorm(10)
)
rec <- recipes::recipe(outcome ~ x1 + x2, data = df)
rec_trained <- recipes::prep(rec, training = df, retain = TRUE)
expect_warning(
bioLeak:::.bio_validate_recipe_graph(rec_trained, context = "test", mode = "warn"),
"trained recipe"
)
expect_error(
bioLeak:::.bio_validate_recipe_graph(rec_trained, context = "test", mode = "error"),
"trained recipe"
)
})
test_that("recipe leakage validator flags negative lag steps", {
skip_if_not_installed("recipes")
df <- data.frame(
outcome = factor(rep(c(0, 1), each = 5), levels = c(0, 1)),
x1 = rnorm(10),
x2 = rnorm(10)
)
rec_lag <- recipes::recipe(outcome ~ x1 + x2, data = df) |>
recipes::step_lag(x1, lag = -1)
expect_warning(
bioLeak:::.bio_validate_recipe_graph(rec_lag, context = "test", mode = "warn"),
"negative lag"
)
})
test_that("workflow leakage validator flags trained workflows", {
skip_if_not_installed("workflows")
skip_if_not_installed("parsnip")
df <- data.frame(
outcome = factor(rep(c(0, 1), each = 6), levels = c(0, 1)),
x1 = rnorm(12),
x2 = rnorm(12)
)
wf <- workflows::workflow() |>
workflows::add_model(
parsnip::logistic_reg(mode = "classification") |>
parsnip::set_engine("glm")
) |>
workflows::add_formula(outcome ~ x1 + x2)
wf_trained <- workflows::fit(wf, data = df)
expect_warning(
bioLeak:::.bio_validate_workflow_graph(wf_trained, context = "test", mode = "warn"),
"trained workflow"
)
})
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