R Under development (unstable) (2024-06-27 r86847 ucrt) -- "Unsuffered Consequences"
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> if (requireNamespace("testthat", quietly = TRUE)) {
+   library("testthat")
+   library("mlr3learners")
+   test_check("mlr3learners")
+ }
Loading required package: mlr3
WARN  [12:48:54.442] [mlr3] train: one multinomial or binomial class has fewer than 8  observations; dangerous ground
WARN  [12:48:54.707] [mlr3] train: one multinomial or binomial class has fewer than 8  observations; dangerous ground
WARN  [12:48:54.947] [mlr3] train: one multinomial or binomial class has fewer than 8  observations; dangerous ground
WARN  [12:48:55.158] [mlr3] train: one multinomial or binomial class has fewer than 8  observations; dangerous ground
WARN  [12:48:55.483] [mlr3] train: one multinomial or binomial class has fewer than 8  observations; dangerous ground
WARN  [12:48:55.485] [mlr3] train: one multinomial or binomial class has fewer than 8  observations; dangerous ground
WARN  [12:48:56.105] [mlr3] train: one multinomial or binomial class has fewer than 8  observations; dangerous ground
WARN  [12:48:56.107] [mlr3] train: one multinomial or binomial class has fewer than 8  observations; dangerous ground
WARN  [12:49:13.344] [mlr3] train: glm.fit: algorithm did not converge
WARN  [12:49:13.345] [mlr3] train: glm.fit: fitted probabilities numerically 0 or 1 occurred
WARN  [12:49:13.416] [mlr3] train: glm.fit: algorithm did not converge
WARN  [12:49:13.418] [mlr3] train: glm.fit: fitted probabilities numerically 0 or 1 occurred
WARN  [12:49:13.484] [mlr3] train: glm.fit: algorithm did not converge
WARN  [12:49:13.486] [mlr3] train: glm.fit: fitted probabilities numerically 0 or 1 occurred
WARN  [12:49:13.588] [mlr3] train: glm.fit: algorithm did not converge
WARN  [12:49:13.590] [mlr3] train: glm.fit: fitted probabilities numerically 0 or 1 occurred
WARN  [12:49:13.708] [mlr3] train: glm.fit: algorithm did not converge
WARN  [12:49:13.710] [mlr3] train: glm.fit: fitted probabilities numerically 0 or 1 occurred
WARN  [12:49:13.783] [mlr3] train: glm.fit: algorithm did not converge
WARN  [12:49:13.784] [mlr3] train: glm.fit: fitted probabilities numerically 0 or 1 occurred
# weights:  18 (10 variable)
initial  value 164.791843 
iter  10 value 16.177348
iter  20 value 7.111438
iter  30 value 6.182999
iter  40 value 5.984028
iter  50 value 5.961278
iter  60 value 5.954900
iter  70 value 5.951851
iter  80 value 5.950343
iter  90 value 5.949904
iter 100 value 5.949867
final  value 5.949867 
stopped after 100 iterations
[ FAIL 0 | WARN 0 | SKIP 3 | PASS 550 ]

══ Skipped tests (3) ═══════════════════════════════════════════════════════════
• On CRAN (3): 'test_classif_nnet.R:2:1', 'test_classif_xgboost.R:2:1',
  'test_regr_xgboost.R:2:1'

[ FAIL 0 | WARN 0 | SKIP 3 | PASS 550 ]
> 
> proc.time()
   user  system elapsed 
  55.84    4.04   59.15