Nothing
test_that("fitting", {
skip_if_not_installed("ClusterR")
set.seed(1234)
spec <- k_means(num_clusters = 3) %>%
set_engine("ClusterR")
expect_no_error(
res <- fit(spec, ~., mtcars)
)
expect_no_error(
res <- fit_xy(spec, mtcars)
)
})
test_that("predicting", {
skip_if_not_installed("ClusterR")
set.seed(1234)
spec <- k_means(num_clusters = 3) %>%
set_engine("ClusterR")
res <- fit(spec, ~., mtcars)
preds <- predict(res, mtcars[c(1:5), ])
expect_identical(
preds,
tibble::tibble(.pred_cluster = factor(paste0("Cluster_", c(1, 1, 1, 2, 2)),
paste0("Cluster_", 1:3)))
)
})
test_that("all levels are preserved with 1 row predictions", {
set.seed(1234)
spec <- k_means(num_clusters = 3) %>%
set_engine("ClusterR")
res <- fit(spec, ~., mtcars)
preds <- predict(res, mtcars[1, ])
expect_identical(
levels(preds$.pred_cluster),
paste0("Cluster_", 1:3)
)
})
test_that("extract_centroids() works", {
skip_if_not_installed("ClusterR")
set.seed(1234)
spec <- k_means(num_clusters = 3) %>%
set_engine("ClusterR")
res <- fit(spec, ~., mtcars)
centroids <- extract_centroids(res)
expected <- vctrs::vec_cbind(
tibble::tibble(.cluster = factor(paste0("Cluster_", 1:3))),
tibble::as_tibble(res$fit$centroids)
)
expect_identical(
centroids,
expected
)
})
test_that("extract_cluster_assignment() works", {
skip_if_not_installed("ClusterR")
set.seed(1234)
spec <- k_means(num_clusters = 3) %>%
set_engine("ClusterR")
res <- fit(spec, ~., mtcars)
clusters <- extract_cluster_assignment(res)
exp_cluster <- res$fit$cluster
exp_cluster <- order(unique(exp_cluster))[exp_cluster]
expected <- vctrs::vec_cbind(
tibble::tibble(.cluster = factor(paste0("Cluster_", exp_cluster)))
)
expect_identical(
clusters,
expected
)
})
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