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test_that("classif_RRF", {
suppressMessages(requirePackages("RRF", default.method = "load"))
parset.list = list(
list(),
list(ntree = 50, mtry = 2),
list(ntree = 50, mtry = 4)
)
old.predicts.list = list()
old.probs.list = list()
for (i in seq_along(parset.list)) {
parset = parset.list[[i]]
pars = list(formula = multiclass.formula, data = multiclass.train)
pars = c(pars, parset)
set.seed(getOption("mlr.debug.seed"))
m = do.call(RRF::RRF, pars)
p = predict(m, newdata = multiclass.test, type = "response")
p2 = predict(m, newdata = multiclass.test, type = "prob")
old.predicts.list[[i]] = p
old.probs.list[[i]] = p2
}
testSimpleParsets("classif.RRF", multiclass.df, multiclass.target,
multiclass.train.inds, old.predicts.list, parset.list)
testProbParsets("classif.RRF", multiclass.df, multiclass.target,
multiclass.train.inds, old.probs.list, parset.list)
tt = RRF::RRF
testCVParsets("classif.RRF", multiclass.df, multiclass.target, tune.train = tt,
parset.list = parset.list)
})
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