skip_connection("ml-classification-linear-svc")
skip_on_livy()
skip_on_arrow_devel()
skip_databricks_connect()
test_that("ml_linear_svc() default params", {
test_requires_version("3.0.0")
sc <- testthat_spark_connection()
test_default_args(sc, ml_linear_svc)
})
test_that("ml_linear_svc() param setting", {
test_requires_version("3.0.0")
sc <- testthat_spark_connection()
test_args <- list(
fit_intercept = FALSE,
reg_param = 1e-4,
max_iter = 50,
standardization = FALSE,
tol = 1e-05,
threshold = 0.6,
aggregation_depth = 3,
features_col = "fcol",
label_col = "lcol",
prediction_col = "pcol",
raw_prediction_col = "rpcol"
)
test_param_setting(sc, ml_linear_svc, test_args)
})
test_that("ml_linear_svc() runs", {
test_requires_version("2.2.0")
sc <- testthat_spark_connection()
iris_tbl2 <- testthat_tbl("iris") %>%
mutate(is_versicolor = ifelse(
Species == "versicolor", "versicolor", "other"
)) %>%
select(-Species)
expect_error(
ml_linear_svc(iris_tbl2, is_versicolor ~ .) %>%
ml_predict(iris_tbl2) %>%
pull(predicted_label),
NA
)
})
test_clear_cache()
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