@@ -10,7 +10,7 @@ test_that("Stacking Pipeline", {
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# default
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graph_stack = pipeline_stacking(base_learners , super_learner )
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expect_graph(graph_stack )
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- expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion " , " super.rpart" ))
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+ expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion_stacking " , " super.rpart" ))
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graph_learner = as_learner(graph_stack )
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graph_learner $ train(tsk(" iris" ))
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expect_class(graph_learner $ model $ super.rpart $ model , " rpart" )
@@ -19,7 +19,7 @@ test_that("Stacking Pipeline", {
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# no nop
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graph_stack = pipeline_stacking(base_learners , super_learner , use_features = FALSE )
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expect_graph(graph_stack )
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- expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " featureunion " , " super.rpart" ))
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+ expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " featureunion_stacking " , " super.rpart" ))
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graph_learner = as_learner(graph_stack )
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graph_learner $ train(tsk(" iris" ))
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expect_class(graph_learner $ model $ super.rpart $ model , " rpart" )
@@ -28,7 +28,7 @@ test_that("Stacking Pipeline", {
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# folds
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graph_stack = pipeline_stacking(base_learners , super_learner , folds = 5 )
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expect_graph(graph_stack )
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- expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion " , " super.rpart" ))
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+ expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion_stacking " , " super.rpart" ))
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graph_learner = as_learner(graph_stack )
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graph_learner $ train(tsk(" iris" ))
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expect_equal(graph_learner $ graph $ pipeops $ base.rpart $ param_set $ values $ resampling.folds , 5 )
@@ -38,7 +38,7 @@ test_that("Stacking Pipeline", {
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# insample
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graph_stack = pipeline_stacking(base_learners , super_learner , method = " insample" )
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expect_graph(graph_stack )
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- expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion " , " super.rpart" ))
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+ expect_names(graph_stack $ ids(), identical.to = c(" base.rpart" , " nop" , " featureunion_stacking " , " super.rpart" ))
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graph_learner = as_learner(graph_stack )
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graph_learner $ train(tsk(" iris" ))
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expect_equal(graph_learner $ graph $ pipeops $ base.rpart $ param_set $ values $ resampling.method , " insample" )
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