CRAN Package Check Results for Package mlr3benchmark

Last updated on 2026-08-04 21:51:58 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1.7 7.25 70.93 78.18 ERROR
r-devel-linux-x86_64-debian-gcc 0.1.7 5.10 51.76 56.86 ERROR
r-devel-linux-x86_64-fedora-clang 0.1.7 11.00 104.76 115.76 ERROR
r-devel-linux-x86_64-fedora-gcc 0.1.7 52.66 ERROR
r-devel-windows-x86_64 0.1.7 9.00 74.00 83.00 ERROR
r-patched-linux-x86_64 0.1.7 6.17 63.94 70.11 ERROR
r-release-linux-x86_64 0.1.7 5.73 64.63 70.36 ERROR
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 9.00 76.00 85.00 ERROR
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 97.00 108.00 ERROR

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 Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 0.1.7
Check: tests
Result: ERROR Running ‘testthat.R’ [8s/13s] 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 [06:55:02.225] [mlr3] Running benchmark with 18 resampling iterations INFO [06:55:03.038] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [06:55:03.196] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [06:55:03.288] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [06:55:03.381] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [06:55:03.483] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [06:55:03.577] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [06:55:03.672] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [06:55:03.764] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [06:55:03.854] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [06:55:03.946] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [06:55:04.047] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [06:55:04.167] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [06:55:04.274] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [06:55:04.401] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [06:55:04.487] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [06:55:04.548] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [06:55:04.608] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [06:55:04.735] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [06:55:04.892] [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-clang

Version: 0.1.7
Check: tests
Result: ERROR Running ‘testthat.R’ [6s/7s] 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 [18:12:52.134] [mlr3] Running benchmark with 18 resampling iterations INFO [18:12:52.631] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [18:12:52.732] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [18:12:52.786] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [18:12:52.823] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [18:12:52.864] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [18:12:52.900] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [18:12:52.935] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [18:12:53.005] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [18:12:53.042] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [18:12:53.078] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [18:12:53.146] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [18:12:53.220] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [18:12:53.282] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [18:12:53.356] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [18:12:53.461] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [18:12:53.519] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [18:12:53.565] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [18:12:53.620] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [18:12:53.694] [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, r-devel-windows-x86_64, r-release-windows-x86_64, r-oldrel-windows-x86_64

Version: 0.1.7
Check: tests
Result: ERROR Running ‘testthat.R’ [13s/15s] 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 [17:10:34.245] [mlr3] Running benchmark with 18 resampling iterations INFO [17:10:34.875] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [17:10:34.994] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [17:10:35.059] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [17:10:35.131] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [17:10:35.212] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [17:10:35.282] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [17:10:35.357] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [17:10:35.431] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [17:10:35.511] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [17:10:35.583] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [17:10:35.655] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [17:10:35.729] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [17:10:35.783] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [17:10:35.873] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [17:10:35.964] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [17:10:36.052] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [17:10:36.140] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [17:10:36.227] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [17:10:36.330] [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’ [6s/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 [17:23:46.483] [mlr3] Running benchmark with 18 resampling iterations INFO [17:23:47.740] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [17:23:47.827] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [17:23:47.869] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [17:23:47.917] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [17:23:47.997] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [17:23:48.067] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [17:23:48.134] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [17:23:48.194] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [17:23:48.262] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [17:23:48.338] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [17:23:48.428] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [17:23:48.513] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [17:23:48.583] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [17:23:48.676] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [17:23:48.756] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [17:23:48.836] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [17:23:48.920] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [17:23:49.042] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [17:23:49.146] [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

Version: 0.1.7
Check: tests
Result: ERROR Running 'testthat.R' [6s] 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 [12:46:11.596] [mlr3] Running benchmark with 18 resampling iterations INFO [12:46:11.771] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [12:46:11.840] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [12:46:11.887] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [12:46:11.931] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [12:46:11.981] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [12:46:12.027] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [12:46:12.077] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [12:46:12.107] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [12:46:12.147] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [12:46:12.201] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [12:46:12.245] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [12:46:12.290] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [12:46:12.319] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [12:46:12.369] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [12:46:12.425] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [12:46:12.466] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [12:46:12.519] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [12:46:12.574] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [12:46:12.643] [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-windows-x86_64

Version: 0.1.7
Check: tests
Result: ERROR Running ‘testthat.R’ [8s/11s] 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 [18:03:08.910] [mlr3] Running benchmark with 18 resampling iterations INFO [18:03:09.386] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [18:03:09.459] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [18:03:09.535] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [18:03:09.594] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [18:03:09.648] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [18:03:09.713] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [18:03:09.761] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [18:03:09.808] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [18:03:09.854] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [18:03:09.903] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [18:03:09.961] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [18:03:10.072] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [18:03:10.129] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [18:03:10.191] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [18:03:10.286] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [18:03:10.372] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [18:03:10.464] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [18:03:10.582] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [18:03:10.729] [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-patched-linux-x86_64

Version: 0.1.7
Check: tests
Result: ERROR Running ‘testthat.R’ [7s/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 [18:05:27.535] [mlr3] Running benchmark with 18 resampling iterations INFO [18:05:27.935] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [18:05:28.008] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [18:05:28.046] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [18:05:28.110] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [18:05:28.167] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [18:05:28.210] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [18:05:28.265] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [18:05:28.307] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [18:05:28.350] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [18:05:28.392] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [18:05:28.430] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [18:05:28.499] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [18:05:28.548] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [18:05:28.603] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [18:05:28.661] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [18:05:28.719] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [18:05:28.800] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [18:05:28.868] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [18:05:28.940] [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-release-linux-x86_64

Version: 0.1.7
Check: tests
Result: ERROR Running 'testthat.R' [6s] 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 [12:47:09.255] [mlr3] Running benchmark with 18 resampling iterations INFO [12:47:09.554] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [12:47:09.601] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [12:47:09.644] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [12:47:09.685] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [12:47:09.733] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [12:47:09.778] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [12:47:09.823] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [12:47:09.865] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [12:47:09.913] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [12:47:09.971] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [12:47:10.010] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [12:47:10.036] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [12:47:10.059] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [12:47:10.097] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [12:47:10.140] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [12:47:10.192] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [12:47:10.250] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [12:47:10.297] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [12:47:10.342] [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-release-windows-x86_64

Version: 0.1.7
Check: tests
Result: ERROR Running 'testthat.R' [10s] 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 [03:35:32.769] [mlr3] Running benchmark with 18 resampling iterations INFO [03:35:33.029] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3) INFO [03:35:33.129] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3) INFO [03:35:33.166] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3) INFO [03:35:33.217] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3) INFO [03:35:33.290] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3) INFO [03:35:33.356] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3) INFO [03:35:33.406] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 1/3) INFO [03:35:33.464] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 2/3) INFO [03:35:33.529] [mlr3] Applying learner 'rpart2' on task 'iris' (iter 3/3) INFO [03:35:33.596] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3) INFO [03:35:33.662] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3) INFO [03:35:33.706] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3) INFO [03:35:33.756] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3) INFO [03:35:33.851] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3) INFO [03:35:33.950] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3) INFO [03:35:34.030] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 1/3) INFO [03:35:34.100] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 2/3) INFO [03:35:34.177] [mlr3] Applying learner 'rpart2' on task 'sonar' (iter 3/3) INFO [03:35:34.269] [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-oldrel-windows-x86_64