context("classif_obliqueRF")
test_that("classif_obliqueRF", {
requirePackages("obliqueRF", default.method = "load")
parset.list = list(
list(),
list(ntree = 5L, mtry = 2L),
list(training_method = "svm")
)
old.predicts.list = list()
old.probs.list = list()
for (i in seq_along(parset.list)) {
parset = parset.list[[i]]
train = binaryclass.train
target = train[, binaryclass.target]
target = ifelse(target == binaryclass.task$task.desc$positive, 1, 0)
train[, binaryclass.target] = NULL
train = as.matrix(train)
pars = list(x = train, y = target)
pars = c(pars, parset)
set.seed(getOption("mlr.debug.seed"))
m = do.call(obliqueRF::obliqueRF, pars)
binaryclass.test[, binaryclass.target] = NULL
p = predict(m, newdata = binaryclass.test)
p = as.factor(p)
p = as.factor(ifelse(p == 1L, binaryclass.task$task.desc$positive, binaryclass.task$task.desc$negative))
p2 = predict(m, newdata = binaryclass.test, type = "prob")
p2 = p2[, colnames(p2) == "1"]
old.predicts.list[[i]] = p
old.probs.list[[i]] = p2
}
testSimpleParsets("classif.obliqueRF", binaryclass.df, binaryclass.target,
binaryclass.train.inds, old.predicts.list, parset.list)
testProbParsets("classif.obliqueRF", binaryclass.df, binaryclass.target,
binaryclass.train.inds, old.probs.list, parset.list)
})
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