Running ‘testthat.R’ [88s/124s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
  > library(testthat)
  > library(smartdata)
  Loading required package: mice
  
  Attaching package: 'mice'
  
  The following object is masked from 'package:stats':
  
      filter
  
  The following objects are masked from 'package:base':
  
      cbind, rbind
  
  > 
  > test_check("smartdata")
  ── FAILURE (testFeatSelection.R:20:3): Correct feature selection ───────────────
  `feature_selection(...)` threw an error.
  Message: cannot xtfrm 'x'
  Class:   simpleError/error/condition
  Backtrace:
       █
    1. ├─testthat::expect_error(...) testFeatSelection.R:20:2
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat:::.capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─smartdata::feature_selection(...)
    7.   ├─smartdata:::preprocess(task)
    8.   └─smartdata:::preprocess.featureSelection(task)
    9.     ├─smartdata:::doFeatSelection(task)
   10.     └─smartdata:::doFeatSelection.FSelector(task)
   11.       └─FSelector::cutoff.k(weights, num_features)
   12.         └─base::order(attrs, decreasing = TRUE)
   13.           └─base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   14.             └─base:::FUN(X[[i]], ...)
   15.               ├─base::as.vector(xtfrm(x))
   16.               ├─base::xtfrm(x)
   17.               └─base::xtfrm.default(x)
  
  ── FAILURE (testFeatSelection.R:21:3): Correct feature selection ───────────────
  `feature_selection(...)` threw an error.
  Message: cannot xtfrm 'x'
  Class:   simpleError/error/condition
  Backtrace:
       █
    1. ├─testthat::expect_error(...) testFeatSelection.R:21:2
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat:::.capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─smartdata::feature_selection(...)
    7.   ├─smartdata:::preprocess(task)
    8.   └─smartdata:::preprocess.featureSelection(task)
    9.     ├─smartdata:::doFeatSelection(task)
   10.     └─smartdata:::doFeatSelection.FSelector(task)
   11.       └─FSelector::cutoff.k(weights, num_features)
   12.         └─base::order(attrs, decreasing = TRUE)
   13.           └─base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   14.             └─base:::FUN(X[[i]], ...)
   15.               ├─base::as.vector(xtfrm(x))
   16.               ├─base::xtfrm(x)
   17.               └─base::xtfrm.default(x)
  
  ── FAILURE (testFeatSelection.R:24:3): Correct feature selection ───────────────
  `feature_selection(...)` threw an error.
  Message: cannot xtfrm 'x'
  Class:   simpleError/error/condition
  Backtrace:
       █
    1. ├─testthat::expect_error(...) testFeatSelection.R:24:2
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat:::.capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─smartdata::feature_selection(...)
    7.   ├─smartdata:::preprocess(task)
    8.   └─smartdata:::preprocess.featureSelection(task)
    9.     ├─smartdata:::doFeatSelection(task)
   10.     └─smartdata:::doFeatSelection.FSelector(task)
   11.       └─FSelector::cutoff.k(weights, num_features)
   12.         └─base::order(attrs, decreasing = TRUE)
   13.           └─base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   14.             └─base:::FUN(X[[i]], ...)
   15.               ├─base::as.vector(xtfrm(x))
   16.               ├─base::xtfrm(x)
   17.               └─base::xtfrm.default(x)
  
  ── FAILURE (testFeatSelection.R:25:3): Correct feature selection ───────────────
  `feature_selection(...)` threw an error.
  Message: cannot xtfrm 'x'
  Class:   simpleError/error/condition
  Backtrace:
       █
    1. ├─testthat::expect_error(...) testFeatSelection.R:25:2
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat:::.capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─smartdata::feature_selection(...)
    7.   ├─smartdata:::preprocess(task)
    8.   └─smartdata:::preprocess.featureSelection(task)
    9.     ├─smartdata:::doFeatSelection(task)
   10.     └─smartdata:::doFeatSelection.FSelector(task)
   11.       └─FSelector::cutoff.k(weights, num_features)
   12.         └─base::order(attrs, decreasing = TRUE)
   13.           └─base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   14.             └─base:::FUN(X[[i]], ...)
   15.               ├─base::as.vector(xtfrm(x))
   16.               ├─base::xtfrm(x)
   17.               └─base::xtfrm.default(x)
  
  ── FAILURE (testFeatSelection.R:26:3): Correct feature selection ───────────────
  `feature_selection(...)` threw an error.
  Message: cannot xtfrm 'x'
  Class:   simpleError/error/condition
  Backtrace:
       █
    1. ├─testthat::expect_error(...) testFeatSelection.R:26:2
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat:::.capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─smartdata::feature_selection(...)
    7.   ├─smartdata:::preprocess(task)
    8.   └─smartdata:::preprocess.featureSelection(task)
    9.     ├─smartdata:::doFeatSelection(task)
   10.     └─smartdata:::doFeatSelection.FSelector(task)
   11.       └─FSelector::cutoff.k(weights, num_features)
   12.         └─base::order(attrs, decreasing = TRUE)
   13.           └─base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   14.             └─base:::FUN(X[[i]], ...)
   15.               ├─base::as.vector(xtfrm(x))
   16.               ├─base::xtfrm(x)
   17.               └─base::xtfrm.default(x)
  
  ── FAILURE (testFeatSelection.R:27:3): Correct feature selection ───────────────
  `feature_selection(...)` threw an error.
  Message: cannot xtfrm 'x'
  Class:   simpleError/error/condition
  Backtrace:
       █
    1. ├─testthat::expect_error(...) testFeatSelection.R:27:2
    2. │ └─testthat:::quasi_capture(...)
    3. │   ├─testthat:::.capture(...)
    4. │   │ └─base::withCallingHandlers(...)
    5. │   └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
    6. └─smartdata::feature_selection(...)
    7.   ├─smartdata:::preprocess(task)
    8.   └─smartdata:::preprocess.featureSelection(task)
    9.     ├─smartdata:::doFeatSelection(task)
   10.     └─smartdata:::doFeatSelection.FSelector(task)
   11.       └─FSelector::cutoff.k(weights, num_features)
   12.         └─base::order(attrs, decreasing = TRUE)
   13.           └─base::lapply(z, function(x) if (is.object(x)) as.vector(xtfrm(x)) else x)
   14.             └─base:::FUN(X[[i]], ...)
   15.               ├─base::as.vector(xtfrm(x))
   16.               ├─base::xtfrm(x)
   17.               └─base::xtfrm.default(x)
  
  ── Warning (testMissingValues.R:17:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:18:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:19:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:20:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:21:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  The response has five or fewer unique values.  Are you sure you want to do regression?
  
  ── Warning (testMissingValues.R:22:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:23:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:24:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:25:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:26:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:27:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:28:3): Correct imputation of missing values ────
  glm.fit: algorithm did not converge
  
  ── Warning (testMissingValues.R:28:3): Correct imputation of missing values ────
  glm.fit: fitted probabilities numerically 0 or 1 occurred
  
  ── Warning (testMissingValues.R:28:3): Correct imputation of missing values ────
  glm.fit: algorithm did not converge
  
  ── Warning (testMissingValues.R:28:3): Correct imputation of missing values ────
  glm.fit: fitted probabilities numerically 0 or 1 occurred
  
  ── Warning (testMissingValues.R:28:3): Correct imputation of missing values ────
  glm.fit: algorithm did not converge
  
  ── Warning (testMissingValues.R:28:3): Correct imputation of missing values ────
  glm.fit: fitted probabilities numerically 0 or 1 occurred
  
  ── Warning (testMissingValues.R:28:3): Correct imputation of missing values ────
  glm.fit: algorithm did not converge
  
  ── Warning (testMissingValues.R:28:3): Correct imputation of missing values ────
  glm.fit: fitted probabilities numerically 0 or 1 occurred
  
  ── Warning (testMissingValues.R:28:3): Correct imputation of missing values ────
  Number of logged events: 2
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  lmer does not run. Simplify imputation model
  
  ── Warning (testMissingValues.R:36:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:40:3): Correct imputation of missing values ────
  Number of logged events: 1
  
  ── Warning (testMissingValues.R:41:3): Correct imputation of missing values ────
  Number of logged events: 1
  
    missForest iteration 1 in progress...done!
    missForest iteration 2 in progress...done!
    missForest iteration 3 in progress...done!
    missForest iteration 4 in progress...done!
  [1] "ANS is done"
  [1] "0 samples filtered by NEATER"
  [1] "SLS done"
  finding neighbours
  calculating weights
  computing coordinates
  Possible methods are: 'multivariate', 'univariate' 
  For more information do: ?NoiseFiltersR::AENN 
  Parameters for AENN are: 
    * k: Number of nearest neighbors for KNN 
         Default value: 5 
  For more information do: ?NoiseFiltersR::hybridRepairFilter 
  Parameters for hybrid are: 
    * consensus: Use consensus vote if TRUE. Else, use majority vote 
                 Default value: FALSE 
    * action: Strategy to treat noisy instances: 'remove', 'repair', 'hybrid' 
              Default value: remove 
  Possible methods are: 'AENN', 'ENN', 'BBNR', 'DROP1', 'DROP2', 'DROP3', 'EF', 'ENG', 'HARF', 'GE', 'INFFC', 'IPF', 'Mode', 'PF', 'PRISM', 'RNN', 'ORBoost', 'edgeBoost', 'edgeWeight', 'TomekLinks', 'dynamic', 'hybrid', 'saturation', 'consensusSF', 'classificationSF', 'C45robust', 'C45voting', 'C45iteratedVoting', 'CVCF' 
  Possible methods are: 'gibbs_sampling', 'expect_maximization', 'central_imputation', 'knn_imputation', 'rf_imputation', 'PCA_imputation', 'MCA_imputation', 'FAMD_imputation', 'hotdeck', 'iterative_robust', 'regression_imputation', 'ATN' 
  For more information do: ?FSelector::chi.squared 
  Parameters for chi_squared are: 
    * num_features: Number of attributes to pick (apart from class_attr, if supplied). 
                    Should be lower than number of features in the 
                    dataset 
                    Default value: 1 
  Possible methods are: 'CNN', 'ENN', 'multiedit', 'FRIS' 
  Possible methods are: 'chi2', 'chi_merge', 'extended_chi2', 'mod_chi2', 'CAIM', 'CACC', 'ameva', 'mdlp', 'equalfreq', 'equalwidth', 'globalequalwidth' 
  Possible methods are: 'z_score', 'pos_standardization', 'unitization', 'pos_unitization', 'min_max', 'rnorm', 'rpnorm', 'sd_quotient', 'mad_quotient', 'range_quotient', 'max_quotient', 'mean_quotient', 'median_quotient', 'sum_quotient', 'ssq_quotient', 'norm', 'pnorm', 'znorm' 
  Possible methods are: 'RACOG', 'wRACOG', 'PDFOS', 'RWO', 'ADASYN', 'ANSMOTE', 'SMOTE', 'MWMOTE', 'BLSMOTE', 'DBSMOTE', 'SLMOTE', 'RSLSMOTE' 
  Possible methods are: 'lle_knn', 'lle_epsilon', 'adaptative_gpca' 
  ══ testthat results  ═══════════════════════════════════════════════════════════
  FAILURE (testFeatSelection.R:20:3): Correct feature selection
  FAILURE (testFeatSelection.R:21:3): Correct feature selection
  FAILURE (testFeatSelection.R:24:3): Correct feature selection
  FAILURE (testFeatSelection.R:25:3): Correct feature selection
  FAILURE (testFeatSelection.R:26:3): Correct feature selection
  FAILURE (testFeatSelection.R:27:3): Correct feature selection
  Warning (testMissingValues.R:17:3): Correct imputation of missing values
  Warning (testMissingValues.R:18:3): Correct imputation of missing values
  Warning (testMissingValues.R:19:3): Correct imputation of missing values
  Warning (testMissingValues.R:20:3): Correct imputation of missing values
  Warning (testMissingValues.R:21:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:22:3): Correct imputation of missing values
  Warning (testMissingValues.R:23:3): Correct imputation of missing values
  Warning (testMissingValues.R:24:3): Correct imputation of missing values
  Warning (testMissingValues.R:25:3): Correct imputation of missing values
  Warning (testMissingValues.R:26:3): Correct imputation of missing values
  Warning (testMissingValues.R:27:3): Correct imputation of missing values
  Warning (testMissingValues.R:28:3): Correct imputation of missing values
  Warning (testMissingValues.R:28:3): Correct imputation of missing values
  Warning (testMissingValues.R:28:3): Correct imputation of missing values
  Warning (testMissingValues.R:28:3): Correct imputation of missing values
  Warning (testMissingValues.R:28:3): Correct imputation of missing values
  Warning (testMissingValues.R:28:3): Correct imputation of missing values
  Warning (testMissingValues.R:28:3): Correct imputation of missing values
  Warning (testMissingValues.R:28:3): Correct imputation of missing values
  Warning (testMissingValues.R:28:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:36:3): Correct imputation of missing values
  Warning (testMissingValues.R:40:3): Correct imputation of missing values
  Warning (testMissingValues.R:41:3): Correct imputation of missing values
  
  [ FAIL 6 | WARN 88 | SKIP 0 | PASS 231 ]
  Error: Test failures
  Execution halted