test_that("predict on newdata works / clust", {
task = tsk("usarrests")$filter(1:40)
learner = lrn("clust.featureless", num_clusters = 1L)
expect_error(learner$predict(task), "trained")
learner$train(task)
expect_task(learner$state$train_task)
newdata = tsk("usarrests")$filter(41:50)$data()
# passing the task
p = learner$predict_newdata(newdata = newdata, task = task)
expect_data_table(as.data.table(p), nrows = 10)
expect_set_equal(as.data.table(p)$row_ids, 1:10)
expect_null(p$truth)
# rely on internally stored task representation
p = learner$predict_newdata(newdata = newdata, task = NULL)
expect_data_table(as.data.table(p), nrows = 10L)
expect_set_equal(as.data.table(p)$row_ids, 1:10)
expect_null(p$truth)
})
test_that("reset()", {
task = tsk("usarrests")
learner = lrn("clust.featureless", num_clusters = 2L)
learner$train(task)
expect_list(learner$state, names = "unique")
expect_learner(learner$reset())
expect_null(learner$state)
})
test_that("empty predict set (#421)", {
task = tsk("usarrests")
learner = lrn("clust.featureless", num_clusters = 1L)
resampling = rsmp("holdout", ratio = 1)
hout = resampling$instantiate(task)
model = learner$train(task, hout$train_set(1))
pred = learner$predict(task, hout$test_set(1))
expect_match(learner$log$msg, "No data to predict on", fixed = TRUE, all = FALSE)
})
test_that("assignment saving works", {
task = tsk("usarrests")
learner = lrn("clust.featureless")
expect_true(learner$save_assignments)
learner$train(task)
expect_vector(learner$assignments)
expect_length(learner$assignments, task$nrow)
learner$reset()
learner$save_assignments = FALSE
expect_false(learner$save_assignments)
learner$train(task)
expect_null(learner$assignments)
})
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