Nothing
test_that("`class_pred` can be converted to `factor` when computing metrics", {
skip_if_not_installed("probably")
cp_truth <- probably::as_class_pred(two_class_example$truth, which = 1)
cp_estimate <- probably::as_class_pred(two_class_example$predicted, which = 2)
fct_truth <- two_class_example$truth
fct_truth[1] <- NA
fct_estimate <- two_class_example$predicted
fct_estimate[2] <- NA
expect_identical(
accuracy_vec(fct_truth, cp_estimate),
accuracy_vec(fct_truth, fct_estimate)
)
expect_identical(
accuracy_vec(fct_truth, cp_estimate, na_rm = FALSE),
NA_real_
)
expect_snapshot(
error = TRUE,
accuracy_vec(cp_truth, cp_estimate)
)
})
test_that("`class_pred` errors when passed to `conf_mat()`", {
skip_if_not_installed("probably")
cp_hpc_cv <- hpc_cv
cp_hpc_cv$obs <- probably::as_class_pred(cp_hpc_cv$obs, which = 1)
cp_hpc_cv$pred <- probably::as_class_pred(cp_hpc_cv$pred, which = 2)
expect_snapshot(
error = TRUE,
conf_mat(cp_hpc_cv, obs, pred)
)
expect_snapshot(
error = TRUE,
conf_mat(dplyr::group_by(cp_hpc_cv, Resample), obs, pred)
)
})
test_that("`class_pred` errors when passed to `metrics()`", {
skip_if_not_installed("probably")
cp_truth <- probably::as_class_pred(two_class_example$truth, which = 1)
cp_estimate <- probably::as_class_pred(two_class_example$predicted, which = 2)
cp_df <- data.frame(truth = cp_truth, estimate = cp_estimate, class1 = two_class_example$Class1)
expect_snapshot(
error = TRUE,
metrics(cp_df, truth, estimate, class1)
)
})
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