CRAN Package Check Results for Package mlr3benchmark

Last updated on 2026-07-25 14:50:10 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.7 6.52 85.77 92.29 OK
r-devel-linux-x86_64-debian-gcc 0.1.7 5.17 51.22 56.39 ERROR
r-devel-linux-x86_64-fedora-clang 0.1.7 12.00 103.54 115.54 ERROR
r-devel-linux-x86_64-fedora-gcc 0.1.7 48.95 ERROR
r-devel-windows-x86_64 0.1.7 8.00 84.00 92.00 OK
r-patched-linux-x86_64 0.1.7 6.60 76.57 83.17 OK
r-release-linux-x86_64 0.1.7 6.78 77.51 84.29 OK
r-release-macos-arm64 0.1.7 2.00 21.00 23.00 OK
r-release-macos-x86_64 0.1.7 5.00 84.00 89.00 OK
r-release-windows-x86_64 0.1.7 8.00 86.00 94.00 OK
r-oldrel-macos-arm64 0.1.7 OK
r-oldrel-macos-x86_64 0.1.7 4.00 59.00 63.00 OK
r-oldrel-windows-x86_64 0.1.7 11.00 115.00 126.00 OK

Check Details

Version: 0.1.7
Check: examples
Result: ERROR Running examples in ‘mlr3benchmark-Ex.R’ failed The error most likely occurred in: > base::assign(".ptime", proc.time(), pos = "CheckExEnv") > ### Name: BenchmarkAggr > ### Title: Aggregated Benchmark Result Object > ### Aliases: BenchmarkAggr > > ### ** Examples > > # Not restricted to mlr3 objects > df = data.frame(tasks = factor(rep(c("A", "B"), each = 5), + levels = c("A", "B")), + learners = factor(paste0("L", 1:5)), + RMSE = runif(10), MAE = runif(10)) > as_benchmark_aggr(df, task_id = "tasks", learner_id = "learners") <BenchmarkAggr> of 10 rows with 2 tasks, 5 learners and 2 measures tasks learners RMSE MAE <fctr> <fctr> <num> <num> 1: A L1 0.26550866 0.2059746 2: A L2 0.37212390 0.1765568 3: A L3 0.57285336 0.6870228 4: A L4 0.90820779 0.3841037 5: A L5 0.20168193 0.7698414 6: B L1 0.89838968 0.4976992 7: B L2 0.94467527 0.7176185 8: B L3 0.66079779 0.9919061 9: B L4 0.62911404 0.3800352 10: B L5 0.06178627 0.7774452 > > if (requireNamespaces(c("mlr3", "rpart"))) { + library(mlr3) + task = tsks(c("pima", "spam")) + learns = lrns(c("classif.featureless", "classif.rpart")) + bm = benchmark(benchmark_grid(task, learns, rsmp("cv", folds = 2))) + + # coercion + as_benchmark_aggr(bm) + } Warning in data(list = id, package = package, envir = ee) : data set ‘PimaIndiansDiabetes2’ not found Error in UseMethod("as_data_backend") : no applicable method for 'as_data_backend' applied to an object of class "NULL" Calls: tsks ... dictionary_initialize_item -> do.call -> <Anonymous> -> as_data_backend Execution halted Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.1.7
Check: tests
Result: ERROR Running ‘testthat.R’ [6s/8s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > if (requireNamespace("testthat", quietly = TRUE)) { + library("testthat") + library("checkmate") # for more expect_*() functions + library("mlr3benchmark") + test_check("mlr3benchmark") + } Saving _problems/test_BenchmarkAggr-99.R INFO [18:06:18.131] [mlr3] Running benchmark with 18 resampling iterations INFO [18:06:18.267] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [18:06:18.355] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [18:06:18.419] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [18:06:18.480] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [18:06:18.518] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [18:06:18.546] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [18:06:18.573] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [18:06:18.602] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [18:06:18.636] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [18:06:18.664] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [18:06:18.730] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [18:06:18.795] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [18:06:18.858] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [18:06:18.905] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [18:06:18.947] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [18:06:18.995] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [18:06:19.036] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [18:06:19.078] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [18:06:19.132] [mlr3] Finished benchmark [ FAIL 1 | WARN 2 | SKIP 0 | PASS 50 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_BenchmarkAggr.R:99:3'): mlr3 coercions ───────────────────────── Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL" Backtrace: ▆ 1. └─mlr3::tsks(c("pima", "spam")) at test_BenchmarkAggr.R:99:3 2. └─mlr3misc::dictionary_sugar_mget(dict = mlr_tasks, .keys, ...) 3. └─base::lapply(...) 4. └─mlr3misc (local) FUN(X[[i]], ...) 5. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest) 6. └─mlr3misc:::dictionary_initialize_item(key, obj, dots) 7. ├─base::do.call(constructor, cargs) 8. └─mlr3 (local) `<fn>`() 9. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench")) [ FAIL 1 | WARN 2 | SKIP 0 | PASS 50 ] Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-debian-gcc

Version: 0.1.7
Check: examples
Result: ERROR Running examples in ‘mlr3benchmark-Ex.R’ failed The error most likely occurred in: > ### Name: BenchmarkAggr > ### Title: Aggregated Benchmark Result Object > ### Aliases: BenchmarkAggr > > ### ** Examples > > # Not restricted to mlr3 objects > df = data.frame(tasks = factor(rep(c("A", "B"), each = 5), + levels = c("A", "B")), + learners = factor(paste0("L", 1:5)), + RMSE = runif(10), MAE = runif(10)) > as_benchmark_aggr(df, task_id = "tasks", learner_id = "learners") <BenchmarkAggr> of 10 rows with 2 tasks, 5 learners and 2 measures tasks learners RMSE MAE <fctr> <fctr> <num> <num> 1: A L1 0.26550866 0.2059746 2: A L2 0.37212390 0.1765568 3: A L3 0.57285336 0.6870228 4: A L4 0.90820779 0.3841037 5: A L5 0.20168193 0.7698414 6: B L1 0.89838968 0.4976992 7: B L2 0.94467527 0.7176185 8: B L3 0.66079779 0.9919061 9: B L4 0.62911404 0.3800352 10: B L5 0.06178627 0.7774452 > > if (requireNamespaces(c("mlr3", "rpart"))) { + library(mlr3) + task = tsks(c("pima", "spam")) + learns = lrns(c("classif.featureless", "classif.rpart")) + bm = benchmark(benchmark_grid(task, learns, rsmp("cv", folds = 2))) + + # coercion + as_benchmark_aggr(bm) + } Warning in data(list = id, package = package, envir = ee) : data set ‘PimaIndiansDiabetes2’ not found Error in UseMethod("as_data_backend") : no applicable method for 'as_data_backend' applied to an object of class "NULL" Calls: tsks ... dictionary_initialize_item -> do.call -> <Anonymous> -> as_data_backend Execution halted Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Version: 0.1.7
Check: tests
Result: ERROR Running ‘testthat.R’ [12s/14s] Running the tests in ‘tests/testthat.R’ failed. Complete output: > if (requireNamespace("testthat", quietly = TRUE)) { + library("testthat") + library("checkmate") # for more expect_*() functions + library("mlr3benchmark") + test_check("mlr3benchmark") + } Saving _problems/test_BenchmarkAggr-99.R INFO [10:04:45.637] [mlr3] Running benchmark with 18 resampling iterations INFO [10:04:46.385] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [10:04:46.515] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [10:04:46.577] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [10:04:46.637] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [10:04:46.712] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [10:04:46.854] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [10:04:46.998] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [10:04:47.076] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [10:04:47.184] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [10:04:47.252] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [10:04:47.315] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [10:04:47.402] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [10:04:47.461] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [10:04:47.594] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [10:04:47.700] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [10:04:47.789] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [10:04:47.881] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [10:04:47.976] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [10:04:48.083] [mlr3] Finished benchmark [ FAIL 1 | WARN 2 | SKIP 0 | PASS 50 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_BenchmarkAggr.R:99:3'): mlr3 coercions ───────────────────────── Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL" Backtrace: ▆ 1. └─mlr3::tsks(c("pima", "spam")) at test_BenchmarkAggr.R:99:3 2. └─mlr3misc::dictionary_sugar_mget(dict = mlr_tasks, .keys, ...) 3. └─base::lapply(...) 4. └─mlr3misc (local) FUN(X[[i]], ...) 5. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest) 6. └─mlr3misc:::dictionary_initialize_item(key, obj, dots) 7. ├─base::do.call(constructor, cargs) 8. └─mlr3 (local) `<fn>`() 9. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench")) [ FAIL 1 | WARN 2 | SKIP 0 | PASS 50 ] Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-fedora-clang

Version: 0.1.7
Check: tests
Result: ERROR Running ‘testthat.R’ Running the tests in ‘tests/testthat.R’ failed. Complete output: > if (requireNamespace("testthat", quietly = TRUE)) { + library("testthat") + library("checkmate") # for more expect_*() functions + library("mlr3benchmark") + test_check("mlr3benchmark") + } Saving _problems/test_BenchmarkAggr-99.R INFO [08:21:52.146] [mlr3] Running benchmark with 18 resampling iterations INFO [08:21:52.461] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [08:21:52.508] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [08:21:52.533] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [08:21:52.558] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [08:21:52.594] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [08:21:52.622] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [08:21:52.652] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [08:21:52.682] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [08:21:52.712] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [08:21:52.742] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [08:21:52.769] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [08:21:52.812] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [08:21:52.858] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [08:21:52.902] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [08:21:52.940] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [08:21:52.976] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [08:21:53.012] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [08:21:53.050] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [08:21:53.105] [mlr3] Finished benchmark [ FAIL 1 | WARN 2 | SKIP 0 | PASS 50 ] ══ Failed tests ════════════════════════════════════════════════════════════════ ── Error ('test_BenchmarkAggr.R:99:3'): mlr3 coercions ───────────────────────── Error in `UseMethod("as_data_backend")`: no applicable method for 'as_data_backend' applied to an object of class "NULL" Backtrace: ▆ 1. └─mlr3::tsks(c("pima", "spam")) at test_BenchmarkAggr.R:99:3 2. └─mlr3misc::dictionary_sugar_mget(dict = mlr_tasks, .keys, ...) 3. └─base::lapply(...) 4. └─mlr3misc (local) FUN(X[[i]], ...) 5. └─mlr3misc:::dictionary_get(dict, .key, .dicts_suggest = .dicts_suggest) 6. └─mlr3misc:::dictionary_initialize_item(key, obj, dots) 7. ├─base::do.call(constructor, cargs) 8. └─mlr3 (local) `<fn>`() 9. └─mlr3::as_data_backend(load_dataset("PimaIndiansDiabetes2", "mlbench")) [ FAIL 1 | WARN 2 | SKIP 0 | PASS 50 ] Error: ! Test failures. Execution halted Flavor: r-devel-linux-x86_64-fedora-gcc