context("regr_featureless")
test_that("regr_featureless", {
df = data.frame(
y = c(1, 2, 3, 3, 3),
x = rep(1, 5)
)
method = c("mean", "median")
task = makeRegrTask(data = df, target = "y")
# compute predictions manually
expected.response = list(
median = 3,
mean = (1 + 2 + 3 + 3 + 3) / 5
)
for (m in method) {
lrn = makeLearner("regr.featureless", method = m)
mod = train(lrn, task)
# test content of learner model
expect_equal(getLearnerModel(mod)$response, expected.response[[m]])
# test prediction works properly
n = 10
test = data.frame(rep(1, n))
p = predict(mod, newdata = test)
expect_equal(getPredictionResponse(p), rep(expected.response[[m]], n))
# test that printer works correctly
expect_output(print(lrn), "featureless")
expect_output(print(lrn), m)
}
})
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