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
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
|
context("learners_all_surv")
test_that("learners work: surv ", {
requirePackagesOrSkip("Hmisc", default.method = "load")
# settings to make learners faster and deal with small sample size
hyperpars = list(
surv.cforest = list(mtry = 1L)
)
# normal survival analysis
sub.task = subsetTask(surv.task, subset = c(1:70),
features = getTaskFeatureNames(surv.task)[c(1, 2)])
lrns = listLearnersCustom("surv", create = TRUE)
lapply(lrns, testThatLearnerParamDefaultsAreInParamSet)
lapply(lrns, testBasicLearnerProperties, task = sub.task,
hyperpars = hyperpars)
# survival analysis with factors
lrns = listLearnersCustom("surv", properties = "factors", create = TRUE)
lapply(lrns, testThatLearnerHandlesFactors, task = sub.task,
hyperpars = hyperpars)
# survival analysis with ordered factors
lrns = listLearnersCustom("surv", properties = "ordered", create = TRUE)
lapply(lrns, testThatLearnerHandlesFactors, task = sub.task,
hyperpars = hyperpars)
# surv with weights
# normal size of surv.task necessary otherwise cvglmnet does not converge
lrns = listLearnersCustom("surv", properties = "weights", create = TRUE)
lapply(lrns, testThatLearnerRespectsWeights, hyperpars = hyperpars,
task = surv.task, train.inds = surv.train.inds,
test.inds = surv.test.inds,
weights = rep(c(1L, 5L), length.out = length(surv.train.inds)),
pred.type = "response", get.pred.fun = getPredictionResponse)
# survival with missings
lrns = listLearnersCustom("surv", properties = "missings", create = TRUE)
lapply(lrns, testThatLearnerHandlesMissings, task = sub.task,
hyperpars = hyperpars)
# surv with oobpreds
lrns = listLearnersCustom("surv", properties = "oobpreds", create = TRUE)
lapply(lrns, testThatGetOOBPredsWorks, task = sub.task)
# survival variable importance
lrns = listLearnersCustom("surv", properties = "featimp", create = TRUE)
lapply(lrns, testThatLearnerHandlesMissings, task = surv.task,
hyperpars = hyperpars)
lapply(lrns, testThatLearnerCanCalculateImportance, task = surv.task,
hyperpars = hyperpars)
})
|
