Nothing
task = tsk("rats")$filter(sample(300, 50))
task_regr = tgen("friedman1")$generate(20)
test_that("crankcompositor", {
pipe = mlr3pipelines::ppl("crankcompositor", learner = lrn("surv.kaplan"))
expect_class(pipe, "Graph")
pipe = mlr3pipelines::ppl("crankcompositor", learner = lrn("surv.kaplan"), graph_learner = TRUE)
expect_class(pipe, "GraphLearner")
pipe$train(task)
p = pipe$predict(task)
expect_prediction_surv(p)
expect_true("crank" %in% p$predict_types)
})
test_that("distrcompositor", {
pipe = mlr3pipelines::ppl("distrcompositor", learner = lrn("surv.rpart"))
expect_class(pipe, "Graph")
pipe = mlr3pipelines::ppl("distrcompositor", learner = lrn("surv.rpart"), graph_learner = TRUE)
expect_class(pipe, "GraphLearner")
p = pipe$train(task)$predict(task)
expect_prediction_surv(p)
expect_true("distr" %in% p$predict_types)
})
test_that("survaverager", {
pipe = mlr3pipelines::ppl("survaverager", learners = list(lrn("surv.kaplan"),
lrn("surv.kaplan", id = "k2")))
expect_class(pipe, "Graph")
pipe = mlr3pipelines::ppl("survaverager", learners = list(lrn("surv.kaplan"),
lrn("surv.kaplan", id = "k2")),
graph_learner = TRUE)
expect_class(pipe, "GraphLearner")
expect_prediction_surv(pipe$train(task)$predict(task))
})
test_that("survbagging", {
pipe = mlr3pipelines::ppl("survbagging", lrn("surv.kaplan"), iterations = 2)
expect_class(pipe, "Graph")
pipe = mlr3pipelines::ppl("survbagging", lrn("surv.kaplan"), iterations = 2, graph_learner = TRUE)
expect_class(pipe, "GraphLearner")
pipe$train(task)
p = pipe$predict(task)
expect_prediction_surv(p)
})
test_that("resample survtoregr", {
pipe = mlr3pipelines::ppl("survtoregr", method = 1, distrcompose = FALSE, graph_learner = TRUE)
rr = resample(task, pipe, rsmp("cv", folds = 2))
expect_numeric(rr$aggregate())
})
test_that("survtoregr 1", {
pipe = mlr3pipelines::ppl("survtoregr", method = 1, distrcompose = FALSE)
expect_class(pipe, "Graph")
pipe = mlr3pipelines::ppl("survtoregr", method = 1, distrcompose = FALSE, graph_learner = TRUE)
expect_class(pipe, "GraphLearner")
pipe$train(task)
p = pipe$predict(task)
expect_prediction_surv(p)
pipe = mlr3pipelines::ppl("survtoregr", method = 1, distrcompose = TRUE, graph_learner = TRUE)
expect_class(pipe, "GraphLearner")
pipe$train(task)
p = pipe$predict(task)
expect_prediction_surv(p)
expect_true("distr" %in% p$predict_types)
})
test_that("survtoregr 2", {
pipe = mlr3pipelines::ppl("survtoregr", method = 2)
expect_class(pipe, "Graph")
pipe = mlr3pipelines::ppl("survtoregr", method = 2, graph_learner = TRUE)
expect_class(pipe, "GraphLearner")
pipe$train(task)
p = pipe$predict(task)
expect_prediction_surv(p)
expect_true("distr" %in% p$predict_types)
pipe = mlr3pipelines::ppl("survtoregr", method = 2, regr_se_learner = lrn("regr.featureless"),
graph_learner = TRUE)
expect_class(pipe, "GraphLearner")
pipe$train(task)
p = pipe$predict(task)
expect_prediction_surv(p)
expect_true("distr" %in% p$predict_types)
})
test_that("survtoregr 3", {
pipe = mlr3pipelines::ppl("survtoregr", method = 3, distrcompose = FALSE)
expect_class(pipe, "Graph")
pipe = mlr3pipelines::ppl("survtoregr", method = 3, distrcompose = FALSE,
graph_learner = TRUE)
expect_class(pipe, "GraphLearner")
suppressWarnings(pipe$train(task)) # suppress loglik warning
p = pipe$predict(task)
expect_prediction_surv(p)
pipe = mlr3pipelines::ppl("survtoregr", method = 3, distrcompose = TRUE,
graph_learner = TRUE)
expect_class(pipe, "GraphLearner")
suppressWarnings(pipe$train(task)) # suppress loglik warning
p = pipe$predict(task)
expect_prediction_surv(p)
expect_true("distr" %in% p$predict_types)
})
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