@@ -10,7 +10,7 @@ test_that("Stacking Pipeline", {
1010 # default
1111 graph_stack = pipeline_stacking(base_learners , super_learner )
1212 expect_graph(graph_stack )
13- expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion " , " super.rpart" ))
13+ expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion_stacking " , " super.rpart" ))
1414 graph_learner = as_learner(graph_stack )
1515 graph_learner $ train(tsk(" iris" ))
1616 expect_class(graph_learner $ model $ super.rpart $ model , " rpart" )
@@ -19,7 +19,7 @@ test_that("Stacking Pipeline", {
1919 # no nop
2020 graph_stack = pipeline_stacking(base_learners , super_learner , use_features = FALSE )
2121 expect_graph(graph_stack )
22- expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " featureunion " , " super.rpart" ))
22+ expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " featureunion_stacking " , " super.rpart" ))
2323 graph_learner = as_learner(graph_stack )
2424 graph_learner $ train(tsk(" iris" ))
2525 expect_class(graph_learner $ model $ super.rpart $ model , " rpart" )
@@ -28,7 +28,7 @@ test_that("Stacking Pipeline", {
2828 # folds
2929 graph_stack = pipeline_stacking(base_learners , super_learner , folds = 5 )
3030 expect_graph(graph_stack )
31- expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion " , " super.rpart" ))
31+ expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion_stacking " , " super.rpart" ))
3232 graph_learner = as_learner(graph_stack )
3333 graph_learner $ train(tsk(" iris" ))
3434 expect_equal(graph_learner $ graph $ pipeops $ base.rpart $ param_set $ values $ resampling.folds , 5 )
@@ -38,7 +38,7 @@ test_that("Stacking Pipeline", {
3838 # insample
3939 graph_stack = pipeline_stacking(base_learners , super_learner , method = " insample" )
4040 expect_graph(graph_stack )
41- expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion " , " super.rpart" ))
41+ expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion_stacking " , " super.rpart" ))
4242 graph_learner = as_learner(graph_stack )
4343 graph_learner $ train(tsk(" iris" ))
4444 expect_equal(graph_learner $ graph $ pipeops $ base.rpart $ param_set $ values $ resampling.method , " insample" )
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