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test_that("classif_bst", {
requirePackagesOrSkip("bst", default.method = "load")
parset.list1 = list(
list(),
list(cost = 0.6, family = "gaussian"),
list(ctrl = bst::bst_control(mstop = 40L)),
list(learner = "tree", control.tree = list(maxdepth = 2L))
)
parset.list2 = list(
list(),
list(cost = 0.6, family = "gaussian"),
list(mstop = 40L),
list(Learner = "tree", maxdepth = 2L)
)
old.predicts.list = list()
for (i in seq_along(parset.list1)) {
parset = parset.list1[[i]]
parset$y = ifelse(binaryclass.train[, binaryclass.class.col] == binaryclass.class.levs[2], 1, -1)
parset$x = binaryclass.train[, -binaryclass.class.col]
m = do.call(bst::bst, parset)
p = predict(m, binaryclass.test)
old.predicts.list[[i]] = ifelse(p > 0, binaryclass.class.levs[2], binaryclass.class.levs[1])
}
testSimpleParsets("classif.bst", binaryclass.df, binaryclass.target,
binaryclass.train.inds, old.predicts.list, parset.list2)
})
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