Nothing
test_that("autotest", {
learner = lrn("regr.rpart")
expect_learner(learner)
result = run_autotest(learner)
expect_true(result, info = result$error)
exclude = c("formula", "data", "weights", "subset", "na.action", "method", "model",
"x", "y", "parms", "control", "cost", "keep_model")
result = run_paramtest(learner, list(rpart::rpart, rpart::rpart.control), exclude, tag = "train")
expect_true(result, info = result$error)
exclude = c(
"object", # handled internally
"newdata", # handled internally
"type", # handled internally
"na.action" # handled internally
)
result = run_paramtest(learner, rpart:::predict.rpart, exclude, tag = "predict")
expect_true(result, info = result$error)
})
test_that("variable importance", {
task = TaskRegr$new("foo", as_data_backend(cbind(iris, data.frame(unimportant = runif(150)))), target = "Sepal.Length")
learner = lrn("regr.rpart")
learner$train(task)
imp = learner$importance()
expect_numeric(imp, min.len = 1L, any.missing = FALSE)
expect_names(names(imp), subset.of = task$feature_names)
expect_false(is.unsorted(rev(imp)))
})
test_that("selected_features", {
task = TaskRegr$new("foo", as_data_backend(cbind(iris, data.frame(unimportant = runif(150)))), target = "Sepal.Length")
learner = lrn("regr.rpart", maxdepth = 2)
sf = learner$train(task)$selected_features()
expect_subset(sf, task$feature_names, empty.ok = FALSE)
})
test_that("weights", {
task = TaskRegr$new("foo", as_data_backend(cbind(iris, data.frame(w = rep(c(1, 10, 100), each = 50)))), target = "Sepal.Length")
task$set_col_roles("w", character())
learner = lrn("regr.rpart")
learner$train(task)
p1 = learner$predict(task)
task$set_col_roles("w", "weight")
learner$train(task)
p2 = learner$predict(task)
expect_lt(p1$score(), p2$score())
})
test_that("default_values on rpart", {
learner = lrn("regr.rpart")
search_space = ps(
minsplit = p_int(2, 128, logscale = TRUE),
minbucket = p_int(1, 64, logscale = TRUE),
cp = p_dbl(1e-04, 1e-1, logscale = TRUE)
)
task = tsk("pima")
values = default_values(learner, search_space, task)
expect_names(names(values), permutation.of = c("minsplit", "minbucket", "cp"))
})
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