skip_connection("broom-bisecting_kmeans")
skip_on_livy()
skip_on_arrow_devel()
skip_databricks_connect()
test_that("bisecting_kmeans.tidy() works", {
## ---------------- Connection and data upload to Spark ----------------------
sc <- testthat_spark_connection()
test_requires_version("2.0.0")
mtcars_tbl <- testthat_tbl("mtcars")
bk_model <- mtcars_tbl %>%
ml_bisecting_kmeans(~ mpg + cyl, k = 4L, seed = 123)
## ----------------------------- tidy() --------------------------------------
td1 <- tidy(bk_model)
check_tidy(td1,
exp.row = 4,
exp.names = c("mpg", "cyl", "size", "cluster")
)
expect_equal(td1$size, c(11, 9, 7, 5))
## --------------------------- augment() -------------------------------------
au1 <- bk_model %>%
augment() %>%
dplyr::collect()
check_tidy(au1,
exp.row = nrow(mtcars),
exp.name = c(names(mtcars), ".cluster")
)
au2 <- bk_model %>%
augment(newdata = head(mtcars_tbl, 25)) %>%
dplyr::collect()
check_tidy(au2,
exp.row = 25,
exp.name = c(names(mtcars), ".cluster")
)
## ---------------------------- glance() -------------------------------------
gl1 <- glance(bk_model)
if (spark_version(sc) >= "2.3.0") {
check_tidy(gl1,
exp.row = 1,
exp.names = c("k", "wssse", "silhouette")
)
} else {
check_tidy(gl1,
exp.row = 1,
exp.names = c("k", "wssse")
)
}
})
test_clear_cache()
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