1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
|
test_that("regr_gbm", {
requirePackagesOrSkip("gbm", default.method = "load")
parset.list = list(
list(),
list(n.trees = 10, distribution = "gaussian"),
list(interaction.depth = 2, distribution = "gaussian"),
list(distribution = list(name = "quantile", alpha = 0.2))
)
old.predicts.list = list()
for (i in seq_along(parset.list)) {
parset = parset.list[[i]]
pars = list(regr.formula, data = regr.train)
pars = c(pars, parset)
set.seed(getOption("mlr.debug.seed"))
capture.output({
m = do.call(gbm::gbm, pars)
})
p = gbm::predict.gbm(m, newdata = regr.test, n.trees = length(m$trees))
old.predicts.list[[i]] = p
}
# Different way to pass quantile distribution in mlr
parset.list[[4]]$distribution = "quantile"
parset.list[[4]]$alpha = 0.2
testSimpleParsets("regr.gbm", regr.df, regr.target, regr.train.inds,
old.predicts.list, parset.list)
})
test_that("regr_gbm keep.data is passed correctly", {
expect_silent(train(makeLearner("regr.gbm", keep.data = FALSE), regr.task))
expect_silent(train(makeLearner("regr.gbm", keep.data = TRUE), regr.task))
})
|
