skip_if_not_installed("kernlab")
test_that("autotest", {
learner = lrn("clust.kkmeans")
expect_learner(learner)
result = run_autotest(learner)
expect_true(result, info = result$error)
})
test_that("Learner properties are respected", {
task = tsk("usarrests")
learner = lrn("clust.kkmeans")
expect_learner(learner, task)
# test on multiple paramsets
centers = data.frame(matrix(ncol = length(colnames(task$data())), nrow = 4L))
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$UrbanPop = c(60, 54, 53, 69)
parset_list = list(
list(centers = 2L, kernel = "polydot", degree = 2L),
list(centers = centers, kernel = "laplacedot", sigma = 2L),
list(centers = 3L, kernel = "anovadot")
)
for (i in seq_along(parset_list)) {
parset = parset_list[[i]]
learner$param_set$values = parset
p = learner$train(task)$predict(task)
expect_prediction_clust(p)
if ("complete" %chin% learner$properties) {
expect_prediction_complete(p, learner$predict_type)
}
if ("exclusive" %chin% learner$properties) {
expect_prediction_exclusive(p, learner$predict_type)
}
learner$reset()
}
})
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.