Running ‘run-base.R’ [265s/393s]
Running the tests in ‘tests/run-base.R’ failed.
Complete output:
  > library(testthat)
  > test_check("mlr", filter = "base")
  Loading required package: mlr
  Loading required package: ParamHelpers
  1. Failure: BaseEnsemble (@test_base_BaseEnsemble.R#34) ------------------------
  error$message does not match "predict.type".
  Actual value: ""
  
  
  2. Failure: Learner (@test_base_Learner.R#15) ----------------------------------
  error$message does not match "Trying to predict probs, but".
  Actual value: "Error in trainLearner.classif.__mlrmocklearners__3(.learner = structure(list( : \n  foo\n"
  
  
  3. Failure: Learner (@test_base_Learner.R#18) ----------------------------------
  error$message does not match "Trying to predict probs, but".
  Actual value: "Error in trainLearner.classif.__mlrmocklearners__3(.learner = structure(list( : \n  foo\n"
  
  
  4. Failure: calculateConfusionMatrix (@test_base_calculateConfusionMatrix.R#58) 
  error$message does not match "FailureModel".
  Actual value: "Error in lda.default(x, grouping, ...) : \n  variable 1 appears to be constant within groups\n"
  
  
  5. Failure: checkData (@test_base_checkData.R#4) -------------------------------
  error$message does not match "doesn't contain target var: foo".
  Actual value: "Error in lda.default(x, grouping, ...) : \n  variable 1 appears to be constant within groups\n"
  
  
  6. Failure: checkData (@test_base_checkData.R#20) ------------------------------
  error$message does not match "infinite".
  Actual value: "Error in lda.default(x, grouping, ...) : \n  variable 1 appears to be constant within groups\n"
  
  
  7. Failure: checkData (@test_base_checkData.R#25) ------------------------------
  error$message does not match "contains NaN".
  Actual value: "Error in lda.default(x, grouping, ...) : \n  variable 1 appears to be constant within groups\n"
  
  
  8. Failure: checkData (@test_base_checkData.R#47) ------------------------------
  error$message does not match "Unsupported feature type".
  Actual value: "Error in lda.default(x, grouping, ...) : \n  variable 1 appears to be constant within groups\n"
  
  
  9. Failure: checkTaskLearner (@test_base_checkTaskLearner.R#7) -----------------
  error$message does not match "missing values".
  Actual value: "Error in lda.default(x, grouping, ...) : \n  variable 1 appears to be constant within groups\n"
  
  
  10. Failure: checkTaskLearner (@test_base_checkTaskLearner.R#8) ----------------
  error$message does not match "factor inputs".
  Actual value: "Error in lda.default(x, grouping, ...) : \n  variable 1 appears to be constant within groups\n"
  
  
  11. Failure: checkTaskLearner (@test_base_checkTaskLearner.R#9) ----------------
  error$message does not match "is for 'classif'".
  Actual value: "Error in lda.default(x, grouping, ...) : \n  variable 1 appears to be constant within groups\n"
  
  
  12. Failure: checkTaskLearner (@test_base_checkTaskLearner.R#10) ---------------
  error$message does not match "is for 'regr'".
  Actual value: "Error in lda.default(x, grouping, ...) : \n  variable 1 appears to be constant within groups\n"
  
  
  13. Failure: args are passed down to filter methods (@test_base_generateFilterValuesData.R#89) 
  error$message does not match "Please pass extra arguments".
  Actual value: "object '.datatable.aware' not found"
  
  
  14. Failure: errors for unsupported task and feature types (@test_base_generateFilterValuesData.R#112) 
  error$message does not match "Filter(s) 'mrmr', 'linear.correlation' not compatible with task of type 'classif'".
  Actual value: "object '.datatable.aware' not found"
  
  
  15. Failure: errors for unsupported task and feature types (@test_base_generateFilterValuesData.R#113) 
  error$message does not match "Filter(s) 'mrmr', 'carscore' not compatible with features of type 'factors', and 'factors' respectively".
  Actual value: "object '.datatable.aware' not found"
  
  
  16. Failure: errors for unsupported task and feature types (@test_base_generateFilterValuesData.R#114) 
  error$message does not match "Filter(s) 'carscore' not compatible with features of type 'factors' respectively".
  Actual value: "object '.datatable.aware' not found"
  
  
  17. Failure: getFeatureImportance (@test_base_getFeatureImportance.R#35) -------
  error$message does not match "does not support 'featimp'".
  Actual value: "You need to train the learner with parameter 'importance' set to TRUE"
  
  
  18. Failure: removing par settings works (@test_base_hyperpars.R#33) -----------
  error$message does not match "Trying to remove".
  Actual value: "You need to train the learner with parameter 'importance' set to TRUE"
  
  
  19. Failure: removing par settings works (@test_base_hyperpars.R#34) -----------
  error$message does not match "Trying to remove".
  Actual value: "You need to train the learner with parameter 'importance' set to TRUE"
  
  
  20. Failure: over and undersample arg check works (@test_base_imbal_overundersample.R#31) 
  error$message does not match "binary".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  21. Failure: over and undersample arg check works (@test_base_imbal_overundersample.R#32) 
  error$message does not match "binary".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  22. Failure: smote works (@test_base_imbal_smote.R#18) -------------------------
  error$message does not match "minimal class has size 3".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  23. Failure: smote works (@test_base_imbal_smote.R#19) -------------------------
  error$message does not match "minimal class has size 3".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  24. Failure: smote works (@test_base_imbal_smote.R#20) -------------------------
  error$message does not match "minimal class has size 3".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  25. Failure: smote wrapper (@test_base_imbal_smote.R#70) -----------------------
  error$message does not match "when the minimal class has size".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  26. Failure: Impute data frame (@test_base_impute.R#53) ------------------------
  error$message does not match "used for imputation has/have missing values, but learner".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  27. Failure: Impute data frame (@test_base_impute.R#60) ------------------------
  error$message does not match "used for imputation has/have missing values, but learner".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  28. Failure: Impute data frame (@test_base_impute.R#87) ------------------------
  error$message does not match "column types have changed".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  29. Failure: joinClassLevels (@test_base_joinClassLevels.R#6) ------------------
  error$message does not match "existing".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  30. Failure: joinClassLevels (@test_base_joinClassLevels.R#7) ------------------
  error$message does not match "once".
  Actual value: "2 is not feasible for parameter 'alpha'!"
  
  
  31. Failure: mergeBenchmarkResults (@test_base_mergeBenchmarkResults.R#55) -----
  error$message does not match "multiple times".
  Actual value: "All predicted values must be greater or equal -1"
  
  
  32. Failure: mergeBenchmarkResults (@test_base_mergeBenchmarkResults.R#56) -----
  error$message does not match "are missing".
  Actual value: "All predicted values must be greater or equal -1"
  
  
  33. Failure: mergeBenchmarkResults (@test_base_mergeBenchmarkResults.R#79) -----
  error$message does not match "Different task types".
  Actual value: "All predicted values must be greater or equal -1"
  
  
  34. Failure: mergeBenchmarkResults (@test_base_mergeBenchmarkResults.R#85) -----
  error$message does not match "Different resample description".
  Actual value: "All predicted values must be greater or equal -1"
  
  
  35. Failure: mergeSmallFactorLevels (@test_base_mergeSmallFactorLevels.R#21) ---
  error$message does not match "already a level".
  Actual value: "All predicted values must be greater or equal -1"
  
  
  36. Failure: MultilabelClassifierChainsModel (@test_base_multilabel.R#155) -----
  error$message does not match "Must be equal to set".
  Actual value: "All predicted values must be greater or equal -1"
  
  
  37. Failure: MultilabelNestedStackingModel (@test_base_multilabel.R#155) -------
  error$message does not match "Must be equal to set".
  Actual value: "All predicted values must be greater or equal -1"
  
  
  38. Failure: ordered factors (@test_base_orderedfactors.R#13) ------------------
  error$message does not match "has ordered factor".
  Actual value: "All predicted values must be greater or equal -1"
  
  
  39. Failure: performance checks for missing truth col (@test_base_performance.R#87) 
  error$message does not match "need to have a 'truth' col".
  Actual value: "object 'lrn.list' not found"
  
  
  40. Failure: BenchmarkResult (@test_base_plotBMRBoxplots.R#57) -----------------
  error$message does not match "names are not unique".
  Actual value: "Measure auc requires predict type to be: 'prob'!"
  
  
  41. Failure: plotBMRRanksAsBarChart (@test_base_plotBMRRanksAsBarChart.R#45) ---
  error$message does not match "names are not unique".
  Actual value: "Measure auc requires predict type to be: 'prob'!"
  
  
  42. Failure: BenchmarkSummary (@test_base_plotBMRSummary.R#35) -----------------
  error$message does not match "names are not unique".
  Actual value: "Measure auc requires predict type to be: 'prob'!"
  
  
  43. Failure: plotResiduals with BenchmarkResult (@test_base_plotResiduals.R#76) 
  error$message does not match "names are not unique".
  Actual value: "Measure auc requires predict type to be: 'prob'!"
  
  
  44. Failure: resampling, predicting train set works (@test_base_resample.R#61) -
  error$message does not match "not compatible with resampling".
  Actual value: "Prediction was not generated from a ClassifTask, MultilabelTask or ClusterTask!"
  
  
  45. Failure: resample checks constraints (@test_base_resample.R#103) -----------
  error$message does not match "more folds".
  Actual value: "Prediction was not generated from a ClassifTask, MultilabelTask or ClusterTask!"
  
  
  46. Failure: resample checks constraints (@test_base_resample.R#104) -----------
  error$message does not match "more folds".
  Actual value: "Prediction was not generated from a ClassifTask, MultilabelTask or ClusterTask!"
  
  
  47. Failure: resample is extended by an additional measure (@test_base_resample.R#181) 
  error$message does not match "keep.pred".
  Actual value: "Error in (function (train, test, cl, k = 1, l = 0, prob = FALSE, use.all = TRUE)  : \n  no missing values are allowed\n"
  
  
  48. Failure: resample getter work (@test_base_resample_operators.R#10) ---------
  error$message does not match "keep.pred = FALSE".
  Actual value: "Error in (function (train, test, cl, k = 1, l = 0, prob = FALSE, use.all = TRUE)  : \n  no missing values are allowed\n"
  
  
  testthat results ================================================================
  OK: 2662 SKIPPED: 2 FAILED: 48
  1. Failure: BaseEnsemble (@test_base_BaseEnsemble.R#34) 
  2. Failure: Learner (@test_base_Learner.R#15) 
  3. Failure: Learner (@test_base_Learner.R#18) 
  4. Failure: calculateConfusionMatrix (@test_base_calculateConfusionMatrix.R#58) 
  5. Failure: checkData (@test_base_checkData.R#4) 
  6. Failure: checkData (@test_base_checkData.R#20) 
  7. Failure: checkData (@test_base_checkData.R#25) 
  8. Failure: checkData (@test_base_checkData.R#47) 
  9. Failure: checkTaskLearner (@test_base_checkTaskLearner.R#7) 
  1. ...
  
  Error: testthat unit tests failed
  Execution halted