Last updated on 2024-11-03 11:49:32 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.0.4 | 10.91 | 156.25 | 167.16 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.0.4 | 0.34 | 2.29 | 2.63 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.0.4 | 311.16 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 0.0.4 | 379.38 | OK | |||
| r-devel-windows-x86_64 | 0.0.4 | 11.00 | 314.00 | 325.00 | OK | |
| r-patched-linux-x86_64 | 0.0.4 | 10.05 | 183.71 | 193.76 | OK | |
| r-release-linux-x86_64 | 0.0.4 | 9.85 | 114.85 | 124.70 | ERROR | |
| r-release-macos-arm64 | 0.0.4 | 208.00 | OK | |||
| r-release-macos-x86_64 | 0.0.4 | 361.00 | OK | |||
| r-release-windows-x86_64 | 0.0.4 | 12.00 | 319.00 | 331.00 | OK | |
| r-oldrel-macos-arm64 | 0.0.4 | 153.00 | OK | |||
| r-oldrel-macos-x86_64 | 0.0.4 | 583.00 | OK | |||
| r-oldrel-windows-x86_64 | 0.0.4 | 16.00 | 398.00 | 414.00 | OK |
Version: 0.0.4
Check: whether package can be installed
Result: ERROR
Installation failed.
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.0.4
Check: package dependencies
Result: WARN
Skipping vignette re-building
Packages suggested but not available for checking:
'ParBayesianOptimization', 'quarto'
VignetteBuilder package required for checking but not installed: ‘quarto’
Flavor: r-release-linux-x86_64
Version: 0.0.4
Check: tests
Result: ERROR
Running ‘testthat.R’ [80s/106s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/tests.html
> # * https://testthat.r-lib.org/reference/test_package.html#special-files
>
> library(testthat)
> library(mlexperiments)
>
> test_check("mlexperiments")
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold4
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold5
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold1
CV fold: Fold2
CV fold: Fold3
CV fold: Fold4
CV fold: Fold5
Testing for identical folds in 2 and 1.
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold4
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold5
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold4
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold5
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold4
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold5
Parameter 'ncores' is ignored for learner 'LearnerGlm'.
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold4
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold5
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold1
CV fold: Fold2
CV fold: Fold3
CV fold: Fold1
CV fold: Fold1
CV fold: Fold2
CV fold: Fold3
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerLm'.
CV fold: Fold1
CV fold: Fold2
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Classification: using 'classification error rate' as optimization metric.
Classification: using 'classification error rate' as optimization metric.
Classification: using 'classification error rate' as optimization metric.
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
CV fold: Fold1
Classification: using 'classification error rate' as optimization metric.
Classification: using 'classification error rate' as optimization metric.
Classification: using 'classification error rate' as optimization metric.
CV fold: Fold2
Classification: using 'classification error rate' as optimization metric.
Classification: using 'classification error rate' as optimization metric.
Classification: using 'classification error rate' as optimization metric.
CV fold: Fold3
Classification: using 'classification error rate' as optimization metric.
Classification: using 'classification error rate' as optimization metric.
Classification: using 'classification error rate' as optimization metric.
CV fold: Fold1
CV fold: Fold2
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Regression: using 'mean squared error' as optimization metric.
Regression: using 'mean squared error' as optimization metric.
Regression: using 'mean squared error' as optimization metric.
CV fold: Fold1
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
CV fold: Fold1
Regression: using 'mean squared error' as optimization metric.
Regression: using 'mean squared error' as optimization metric.
Regression: using 'mean squared error' as optimization metric.
CV fold: Fold2
Regression: using 'mean squared error' as optimization metric.
Regression: using 'mean squared error' as optimization metric.
Regression: using 'mean squared error' as optimization metric.
CV fold: Fold3
Regression: using 'mean squared error' as optimization metric.
Regression: using 'mean squared error' as optimization metric.
Regression: using 'mean squared error' as optimization metric.
[ FAIL 7 | WARN 0 | SKIP 1 | PASS 56 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test-lints.R:10:5'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-knn.R:116:5'): test bayesian tuner, initGrid - knn ─────────────
Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
Backtrace:
▆
1. └─knn_optimization$execute(k = 3) at test-knn.R:116:5
2. └─private$select_optimizer(self, private)
3. └─BayesianOptimizer$new(...)
4. └─mlexperiments (local) initialize(...)
── Error ('test-knn.R:184:5'): test bayesian tuner, initPoints - LearnerKnn ────
Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
Backtrace:
▆
1. └─knn_optimization$execute(k = 3) at test-knn.R:184:5
2. └─private$select_optimizer(self, private)
3. └─BayesianOptimizer$new(...)
4. └─mlexperiments (local) initialize(...)
── Error ('test-knn.R:257:5'): test nested cv, bayesian - knn ──────────────────
Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
Backtrace:
▆
1. └─knn_optimization$execute() at test-knn.R:257:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.fold_looper(self, private)
4. ├─base::do.call(private$cv_run_model, run_args)
5. └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<named list>`, fold_test = `<named list>`)
6. ├─base::do.call(.cv_run_nested_model, args)
7. └─mlexperiments (local) `<fn>`(...)
8. └─hparam_tuner$execute(k = self$k_tuning)
9. └─private$select_optimizer(self, private)
10. └─BayesianOptimizer$new(...)
11. └─mlexperiments (local) initialize(...)
── Error ('test-rpart_classification.R:125:5'): test bayesian tuner, initGrid, classification - rpart ──
Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
Backtrace:
▆
1. └─rpart_optimization$execute(k = 3) at test-rpart_classification.R:125:5
2. └─private$select_optimizer(self, private)
3. └─BayesianOptimizer$new(...)
4. └─mlexperiments (local) initialize(...)
── Error ('test-rpart_classification.R:205:5'): test nested cv, bayesian, classification - rpart ──
Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
Backtrace:
▆
1. └─rpart_optimization$execute() at test-rpart_classification.R:205:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.fold_looper(self, private)
4. ├─base::do.call(private$cv_run_model, run_args)
5. └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<named list>`, fold_test = `<named list>`)
6. ├─base::do.call(.cv_run_nested_model, args)
7. └─mlexperiments (local) `<fn>`(...)
8. └─hparam_tuner$execute(k = self$k_tuning)
9. └─private$select_optimizer(self, private)
10. └─BayesianOptimizer$new(...)
11. └─mlexperiments (local) initialize(...)
── Error ('test-rpart_regression.R:125:5'): test bayesian tuner, initGrid, regression - rpart ──
Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
Backtrace:
▆
1. └─rpart_optimization$execute(k = 3) at test-rpart_regression.R:125:5
2. └─private$select_optimizer(self, private)
3. └─BayesianOptimizer$new(...)
4. └─mlexperiments (local) initialize(...)
── Error ('test-rpart_regression.R:203:5'): test nested cv, bayesian, regression - rpart ──
Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.
Backtrace:
▆
1. └─rpart_optimization$execute() at test-rpart_regression.R:203:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.fold_looper(self, private)
4. ├─base::do.call(private$cv_run_model, run_args)
5. └─mlexperiments (local) `<fn>`(train_index = `<int>`, fold_train = `<named list>`, fold_test = `<named list>`)
6. ├─base::do.call(.cv_run_nested_model, args)
7. └─mlexperiments (local) `<fn>`(...)
8. └─hparam_tuner$execute(k = self$k_tuning)
9. └─private$select_optimizer(self, private)
10. └─BayesianOptimizer$new(...)
11. └─mlexperiments (local) initialize(...)
[ FAIL 7 | WARN 0 | SKIP 1 | PASS 56 ]
Error: Test failures
Execution halted
Flavor: r-release-linux-x86_64
Version: 0.0.4
Check: package vignettes
Result: NOTE
Package has ‘vignettes’ subdirectory but apparently no vignettes.
Perhaps the ‘VignetteBuilder’ information is missing from the
DESCRIPTION file?
Flavor: r-release-linux-x86_64