Last updated on 2025-12-25 19:50:20 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.0.8 | 12.01 | 267.49 | 279.50 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.0.8 | 8.19 | 218.41 | 226.60 | OK | |
| r-devel-linux-x86_64-fedora-clang | 0.0.8 | 21.00 | 467.24 | 488.24 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 0.0.8 | 21.00 | 627.98 | 648.98 | OK | |
| r-devel-windows-x86_64 | 0.0.8 | 13.00 | 427.00 | 440.00 | OK | |
| r-patched-linux-x86_64 | 0.0.8 | 10.73 | 271.95 | 282.68 | OK | |
| r-release-linux-x86_64 | 0.0.8 | 11.88 | 281.95 | 293.83 | OK | |
| r-release-macos-arm64 | 0.0.8 | OK | ||||
| r-release-macos-x86_64 | 0.0.8 | 7.00 | 362.00 | 369.00 | OK | |
| r-release-windows-x86_64 | 0.0.8 | 13.00 | 404.00 | 417.00 | OK | |
| r-oldrel-macos-arm64 | 0.0.8 | OK | ||||
| r-oldrel-macos-x86_64 | 0.0.8 | 7.00 | 377.00 | 384.00 | OK | |
| r-oldrel-windows-x86_64 | 0.0.8 | 18.00 | 575.00 | 593.00 | OK |
Version: 0.0.8
Check: examples
Result: ERROR
Running examples in ‘mlexperiments-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: performance
> ### Title: performance
> ### Aliases: performance
>
> ### ** Examples
>
> dataset <- do.call(
+ cbind,
+ c(sapply(paste0("col", 1:6), function(x) {
+ rnorm(n = 500)
+ },
+ USE.NAMES = TRUE,
+ simplify = FALSE
+ ),
+ list(target = sample(0:1, 500, TRUE))
+ ))
>
> fold_list <- splitTools::create_folds(
+ y = dataset[, 7],
+ k = 3,
+ type = "stratified",
+ seed = 123
+ )
>
> glm_optimization <- mlexperiments::MLCrossValidation$new(
+ learner = LearnerGlm$new(),
+ fold_list = fold_list,
+ seed = 123
+ )
>
> glm_optimization$learner_args <- list(family = binomial(link = "logit"))
> glm_optimization$predict_args <- list(type = "response")
> glm_optimization$performance_metric_args <- list(
+ positive = "1",
+ negative = "0"
+ )
> glm_optimization$performance_metric <- list(
+ auc = metric("AUC"), sensitivity = metric("TPR"),
+ specificity = metric("TNR")
+ )
> glm_optimization$return_models <- TRUE
>
> # set data
> glm_optimization$set_data(
+ x = data.matrix(dataset[, -7]),
+ y = dataset[, 7]
+ )
>
> cv_results <- glm_optimization$execute()
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'.
>
> # predictions
> preds <- mlexperiments::predictions(
+ object = glm_optimization,
+ newdata = data.matrix(dataset[, -7]),
+ na.rm = FALSE,
+ ncores = 2L,
+ type = "response"
+ )
Error in `[.data.table`(res, , `:=`(mean = mean(as.numeric(.SD), na.rm = na.rm), :
attempt access index 3/3 in VECTOR_ELT
Calls: <Anonymous> -> [ -> [.data.table
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.0.8
Check: tests
Result: ERROR
Running ‘testthat.R’ [182s/468s]
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
>
> Sys.setenv("OMP_THREAD_LIMIT" = 2)
> Sys.setenv("Ncpu" = 2)
>
> 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'.
Saving _problems/test-glm_predictions-79.R
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'.
Saving _problems/test-glm_predictions-188.R
CV fold: Fold1
CV fold: Fold2
CV fold: Fold3
Registering parallel backend using 2 cores.
Running initial scoring function 11 times in 2 thread(s)... 25.821 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.966 seconds
Noise could not be added to find unique parameter set. Stopping process and returning results so far.
Registering parallel backend using 2 cores.
Running initial scoring function 11 times in 2 thread(s)... 27.299 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.047 seconds
Noise could not be added to find unique parameter set. Stopping process and returning results so far.
Registering parallel backend using 2 cores.
Running initial scoring function 4 times in 2 thread(s)... 12.549 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.107 seconds
3) Running FUN 2 times in 2 thread(s)... 4.992 seconds
CV fold: Fold1
Registering parallel backend using 2 cores.
Running initial scoring function 11 times in 2 thread(s)... 15.024 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.182 seconds
Noise could not be added to find unique parameter set. Stopping process and returning results so far.
CV fold: Fold2
Registering parallel backend using 2 cores.
Running initial scoring function 11 times in 2 thread(s)... 15.514 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.76 seconds
Noise could not be added to find unique parameter set. Stopping process and returning results so far.
CV fold: Fold3
Registering parallel backend using 2 cores.
Running initial scoring function 11 times in 2 thread(s)... 14.044 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.209 seconds
Noise could not be added to find unique parameter set. Stopping process and returning results so far.
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
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.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 25.531 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.07 seconds
3) Running FUN 2 times in 2 thread(s)... 3.963 seconds
Classification: using 'mean misclassification error' as optimization metric.
Classification: using 'mean misclassification error' as optimization metric.
Classification: using 'mean misclassification 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.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 12.95 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.055 seconds
3) Running FUN 2 times in 2 thread(s)... 2.257 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 13.459 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.165 seconds
3) Running FUN 2 times in 2 thread(s)... 2.238 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 14.172 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.91 seconds
3) Running FUN 2 times in 2 thread(s)... 2.592 seconds
CV fold: Fold1
Classification: using 'mean misclassification error' as optimization metric.
Classification: using 'mean misclassification error' as optimization metric.
Classification: using 'mean misclassification error' as optimization metric.
CV fold: Fold2
Classification: using 'mean misclassification error' as optimization metric.
Classification: using 'mean misclassification error' as optimization metric.
Classification: using 'mean misclassification error' as optimization metric.
CV fold: Fold3
Classification: using 'mean misclassification error' as optimization metric.
Classification: using 'mean misclassification error' as optimization metric.
Classification: using 'mean misclassification error' 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.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 6.354 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.301 seconds
3) Running FUN 2 times in 2 thread(s)... 0.677 seconds
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.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 5.334 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.997 seconds
3) Running FUN 2 times in 2 thread(s)... 0.352 seconds
CV fold: Fold2
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 4.992 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.189 seconds
3) Running FUN 2 times in 2 thread(s)... 0.472 seconds
CV fold: Fold3
Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...
... reducing initialization grid to 10 rows.
Registering parallel backend using 2 cores.
Running initial scoring function 10 times in 2 thread(s)... 6.47 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.051 seconds
3) Running FUN 2 times in 2 thread(s)... 0.559 seconds
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 2 | WARN 0 | SKIP 1 | PASS 68 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test-lints.R:10:5'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-glm_predictions.R:73:5'): test predictions, binary - glm ───────
Error in ``[.data.table`(res, , `:=`(mean = mean(as.numeric(.SD), na.rm = na.rm), sd = stats::sd(as.numeric(.SD), na.rm = na.rm)), .SDcols = colnames(res), by = seq_len(nrow(res)))`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. └─mlexperiments::predictions(...) at test-glm_predictions.R:73:5
2. ├─...[]
3. └─data.table:::`[.data.table`(...)
── Error ('test-glm_predictions.R:182:5'): test predictions, regression - lm ───
Error in ``[.data.table`(res, , `:=`(mean = mean(as.numeric(.SD), na.rm = na.rm), sd = stats::sd(as.numeric(.SD), na.rm = na.rm)), .SDcols = colnames(res), by = seq_len(nrow(res)))`: attempt access index 5/5 in VECTOR_ELT
Backtrace:
▆
1. └─mlexperiments::predictions(...) at test-glm_predictions.R:182:5
2. ├─...[]
3. └─data.table:::`[.data.table`(...)
[ FAIL 2 | WARN 0 | SKIP 1 | PASS 68 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang