Nothing
context("clust.cmeans")
skip_if_not_installed("e1071")
test_that("autotest", {
learner = mlr3::lrn("clust.cmeans")
expect_learner(learner)
result = run_autotest(learner)
expect_true(result, info = result$error)
})
test_that("Learner properties are respected", {
task = tsk("usarrests")
learner = mlr_learners$get("clust.cmeans")
expect_learner(learner, task)
# test on multiple paramsets
centers = data.frame(matrix(ncol = length(colnames(task$data())), nrow = 4))
colnames(centers) = colnames(task$data())
centers$Assault = c(100, 200, 150, 300)
centers$Murder = c(11, 3, 10, 5)
centers$Rape = c(20, 18, 10, 26)
centers$UrbanPop = c(60, 54, 53, 69)
parset_list = list(
list(centers = 2L),
list(centers = centers),
list(centers = 2L, dist = "manhattan", m = 3)
)
for (i in seq_along(parset_list)) {
parset = parset_list[[i]]
learner$param_set$values = parset
p = learner$train(task)$predict(task)
expect_prediction_clust(p)
if ("complete" %in% learner$properties) {
expect_prediction_complete(p, learner$predict_type)
}
if ("exclusive" %in% learner$properties) {
expect_prediction_exclusive(p, learner$predict_type)
}
if ("fuzzy" %in% learner$properties) {
expect_prediction_fuzzy(p)
}
}
})
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