Nothing
skip_if_not_installed("ranger")
test_that("autotest", {
learner = mlr3::lrn("regr.ranger", num.trees = 100, importance = "impurity")
expect_learner(learner)
result = run_autotest(learner, N = 50L)
expect_true(result, info = result$error)
})
test_that("hotstart", {
task = tsk("boston_housing")
learner_1 = lrn("regr.ranger", num.trees = 1000L)
learner_1$train(task)
expect_equal(learner_1$state$param_vals$num.trees, 1000L)
expect_equal(learner_1$model$num.trees, 1000L)
hot = HotstartStack$new(learner_1)
learner_2 = lrn("regr.ranger", num.trees = 500L)
expect_equal(hot$start_cost(learner_2, task$hash), 0L)
learner_2$train(task)
expect_equal(learner_2$model$num.trees, 500L)
expect_equal(learner_2$param_set$values$num.trees, 500L)
expect_equal(learner_2$state$param_vals$num.trees, 500L)
learner_3 = lrn("regr.ranger", num.trees = 1500L)
expect_equal(hot$start_cost(learner_3, task$hash), NA_real_)
learner_4 = lrn("regr.ranger", num.trees = 1000L)
expect_equal(hot$start_cost(learner_4, task$hash), -1L)
learner_4$train(task)
expect_equal(learner_4$model$num.trees, 1000L)
expect_equal(learner_4$param_set$values$num.trees, 1000L)
expect_equal(learner_4$state$param_vals$num.trees, 1000L)
})
test_that("mtry.ratio", {
task = mlr3::tsk("mtcars")
learner = mlr3::lrn("regr.ranger", mtry.ratio = 0.5)
res = convert_ratio(learner$param_set$values, "mtry", "mtry.ratio", length(task$feature_names))
expect_equal(
res$mtry,
5
)
expect_null(res$mtry.ratio)
learner$train(task)
expect_equal(
learner$model$mtry,
5
)
})
test_that("default_values", {
learner = lrn("regr.ranger")
search_space = ps(
replace = p_lgl(),
sample.fraction = p_dbl(0.1, 1),
num.trees = p_int(1, 2000),
mtry.ratio = p_dbl(0, 1)
)
task = tsk("pima")
values = default_values(learner, search_space, task)
expect_names(names(values), permutation.of = c("replace", "sample.fraction", "num.trees", "mtry.ratio"))
})
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