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test_that("Nested SpRepCV works without errors", {
data(spatial.task, package = "mlr", envir = environment())
lrn = makeLearner("classif.ranger",
predict.type = "prob")
ps = makeParamSet(makeNumericParam("mtry", lower = 3, upper = 3),
makeNumericParam("num.trees", lower = 10, upper = 10))
ctrl = makeTuneControlRandom(maxit = 1)
inner = makeResampleDesc("SpCV", iters = 2)
wrapper = makeTuneWrapper(lrn, resampling = inner, par.set = ps,
control = ctrl, show.info = FALSE, measures = list(auc))
outer = makeResampleDesc("SpRepCV", folds = 2, reps = 2)
out = suppressMessages(resample(wrapper, spatial.task,
resampling = outer, show.info = TRUE, measures = list(auc)))
expect_atomic_vector(out$measures.test$auc, min.len = 4, max.len = 4)
})
test_that("SpRepCV works without errors", {
data(spatial.task, package = "mlr", envir = environment())
learner = makeLearner("classif.ranger", predict.type = "prob")
resampling = makeResampleDesc("SpRepCV", fold = 2, reps = 2)
out = resample(learner = learner, task = spatial.task,
resampling = resampling, measures = list(auc))
expect_atomic_vector(out$measures.test$auc, min.len = 4, max.len = 4)
})
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