context("multilabel_cforest")
test_that("multilabel_cforest", {
requirePackagesOrSkip("party", default.method = "load")
parset.list = list(
list(),
list(control = party::cforest_unbiased(mtry = 2)),
list(control = party::cforest_unbiased(ntree = 200))
)
parset.list2 = list(
list(),
list(mtry = 2),
list(ntree = 200)
)
old.probs.list = list()
for (i in seq_along(parset.list)) {
parset = parset.list[[i]]
pars = list(multilabel.formula, data = multilabel.train)
pars = c(pars, parset)
set.seed(getOption("mlr.debug.seed"))
m = do.call(party::cforest, pars)
p = predict(m, newdata = multilabel.test) # multivariate cforest can only predict probs
p2 = do.call(rbind, p)
old.probs.list[[i]] = data.frame(p2)
}
testProbParsets("multilabel.cforest", multilabel.df, multilabel.target,
multilabel.train.inds, old.probs.list, parset.list2)
})
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