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test_that("blocking", {
df = multiclass.df
b = as.factor(rep(1:30, 5))
ct = makeClassifTask(target = multiclass.target, data = multiclass.df, blocking = b)
expect_true(getTaskDesc(ct)$has.blocking)
res = makeResampleInstance(makeResampleDesc("CV", iters = 3, blocking.cv = TRUE), task = ct)
for (j in 1:res$desc$iters) {
train.j = res$train.inds[[j]]
test.j = res$test.inds[[j]]
tab = table(b[train.j])
expect_true(setequal(c(0, 5), unique(as.numeric(tab))))
tab = table(b[test.j])
expect_true(setequal(c(0, 5), unique(as.numeric(tab))))
}
# test blocking in resample
lrn = makeLearner("classif.lda")
mycheck = function(rdesc, p, b) {
for (j in 1:rdesc$iters) {
test.j = p$data[p$data$iter == j, "id"]
tab = table(b[test.j])
expect_true(setequal(c(0, 5), unique(as.numeric(tab))))
}
}
rdesc = makeResampleDesc("CV", iters = 3, blocking.cv = TRUE)
p = resample(lrn, ct, rdesc)$pred
mycheck(rdesc, p, b)
rdesc = makeResampleDesc("RepCV", folds = 3, reps = 2, blocking.cv = TRUE)
p = resample(lrn, ct, rdesc)$pred
mycheck(rdesc, p, b)
})
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