Last updated on 2025-09-11 05:48:51 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.0.5 | 6.41 | 173.98 | 180.39 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 0.0.6 | 4.34 | 152.33 | 156.67 | OK | |
| r-devel-linux-x86_64-fedora-clang | 0.0.6 | 241.27 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 0.0.6 | 353.81 | OK | |||
| r-devel-windows-x86_64 | 0.0.5 | 8.00 | 338.00 | 346.00 | OK | |
| r-patched-linux-x86_64 | 0.0.6 | 6.02 | 220.44 | 226.46 | OK | |
| r-release-linux-x86_64 | 0.0.5 | 6.50 | 230.31 | 236.81 | OK | |
| r-release-macos-arm64 | 0.0.6 | 122.00 | OK | |||
| r-release-macos-x86_64 | 0.0.6 | 255.00 | OK | |||
| r-release-windows-x86_64 | 0.0.5 | 9.00 | 333.00 | 342.00 | ERROR | |
| r-oldrel-macos-arm64 | 0.0.6 | 125.00 | OK | |||
| r-oldrel-macos-x86_64 | 0.0.6 | 281.00 | OK | |||
| r-oldrel-windows-x86_64 | 0.0.6 | 9.00 | 449.00 | 458.00 | OK |
Version: 0.0.5
Check: examples
Result: ERROR
Running examples in ‘mlsurvlrnrs-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: LearnerSurvCoxPHCox
> ### Title: R6 Class to construct a Cox proportional hazards survival
> ### learner
> ### Aliases: LearnerSurvCoxPHCox
>
> ### ** Examples
>
> # survival analysis
>
> dataset <- survival::colon |>
+ data.table::as.data.table() |>
+ na.omit()
> dataset <- dataset[get("etype") == 2, ]
>
> seed <- 123
> surv_cols <- c("status", "time", "rx")
>
> feature_cols <- colnames(dataset)[3:(ncol(dataset) - 1)]
>
> split_vector <- splitTools::multi_strata(
+ df = dataset[, .SD, .SDcols = surv_cols],
+ strategy = "kmeans",
+ k = 4
+ )
>
> train_x <- model.matrix(
+ ~ -1 + .,
+ dataset[, .SD, .SDcols = setdiff(feature_cols, surv_cols[1:2])]
+ )
> train_y <- survival::Surv(
+ event = (dataset[, get("status")] |>
+ as.character() |>
+ as.integer()),
+ time = dataset[, get("time")],
+ type = "right"
+ )
>
> fold_list <- splitTools::create_folds(
+ y = split_vector,
+ k = 3,
+ type = "stratified",
+ seed = seed
+ )
>
>
> surv_coxph_cox_optimizer <- mlexperiments::MLCrossValidation$new(
+ learner = LearnerSurvCoxPHCox$new(),
+ fold_list = fold_list,
+ ncores = 1L,
+ seed = seed
+ )
> surv_coxph_cox_optimizer$performance_metric <- c_index
>
> # set data
> surv_coxph_cox_optimizer$set_data(
+ x = train_x,
+ y = train_y
+ )
>
> surv_coxph_cox_optimizer$execute()
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.0.5
Check: tests
Result: ERROR
Running ‘testthat.R’ [107s/357s]
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(mlsurvlrnrs)
>
> test_check("mlsurvlrnrs")
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold1
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 9.369 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.842 seconds
3) Running FUN 2 times in 2 thread(s)... 1.597 seconds
CV fold: Fold2
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 8.916 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 2.764 seconds
3) Running FUN 2 times in 2 thread(s)... 1.55 seconds
CV fold: Fold3
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 10.102 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 1.473 seconds
3) Running FUN 2 times in 2 thread(s)... 1.452 seconds
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)... 6.69 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters... 10.003 seconds
3) Running FUN 2 times in 2 thread(s)... 0.646 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)... 6.522 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 20.965 seconds
3) Running FUN 2 times in 2 thread(s)... 0.58 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)... 7.409 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search... 1.365 seconds
3) Running FUN 2 times in 2 thread(s)... 0.626 seconds
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)... 5.839 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.711 seconds
3) Running FUN 2 times in 2 thread(s)... 0.597 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)... 5.409 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.88 seconds
3) Running FUN 2 times in 2 thread(s)... 0.642 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)... 6.283 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.802 seconds
3) Running FUN 2 times in 2 thread(s)... 0.861 seconds
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)... 6.326 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 16.062 seconds
3) Running FUN 2 times in 2 thread(s)... 0.692 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)... 8.458 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 18.544 seconds
3) Running FUN 2 times in 2 thread(s)... 1.018 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)... 6.263 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 7.886 seconds
3) Running FUN 2 times in 2 thread(s)... 0.564 seconds
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)... 5.434 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters...
- Maximum convergence attempts exceeded - process is probably sampling random points. 75.664 seconds
3) Running FUN 2 times in 2 thread(s)... 0.532 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)... 4.987 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 12.788 seconds
3) Running FUN 2 times in 2 thread(s)... 0.384 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)... 4.657 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 2.726 seconds
3) Running FUN 2 times in 2 thread(s)... 0.437 seconds
[ FAIL 6 | WARN 0 | SKIP 1 | PASS 0 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test-lints.R:10:5'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-surv_coxph_cox.R:56:5'): test cv - surv_coxph_cox ──────────────
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_coxph_cox_optimizer$execute() at test-surv_coxph_cox.R:56:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_glmnet_cox.R:99:5'): test nested cv, grid - surv_glmnet_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_glmnet_cox_optimizer$execute() at test-surv_glmnet_cox.R:99:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_ranger_cox.R:110:5'): test nested cv, bayesian - surv_ranger_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_ranger_cox_optimizer$execute() at test-surv_ranger_cox.R:110:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_rpart_cox.R:108:5'): test nested cv, bayesian - surv_rpart_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_rpart_cox_optimizer$execute() at test-surv_rpart_cox.R:108:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_xgboost_aft.R:116:5'): test nested cv, bayesian - surv_xgboost_aft ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_xgboost_aft_optimizer$execute() at test-surv_xgboost_aft.R:116:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_xgboost_cox.R:115:5'): test nested cv, bayesian - surv_xgboost_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_xgboost_cox_optimizer$execute() at test-surv_xgboost_cox.R:115:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
[ FAIL 6 | WARN 0 | SKIP 1 | PASS 0 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.0.5
Check: examples
Result: ERROR
Running examples in 'mlsurvlrnrs-Ex.R' failed
The error most likely occurred in:
> ### Name: LearnerSurvCoxPHCox
> ### Title: R6 Class to construct a Cox proportional hazards survival
> ### learner
> ### Aliases: LearnerSurvCoxPHCox
>
> ### ** Examples
>
> # survival analysis
>
> dataset <- survival::colon |>
+ data.table::as.data.table() |>
+ na.omit()
> dataset <- dataset[get("etype") == 2, ]
>
> seed <- 123
> surv_cols <- c("status", "time", "rx")
>
> feature_cols <- colnames(dataset)[3:(ncol(dataset) - 1)]
>
> split_vector <- splitTools::multi_strata(
+ df = dataset[, .SD, .SDcols = surv_cols],
+ strategy = "kmeans",
+ k = 4
+ )
>
> train_x <- model.matrix(
+ ~ -1 + .,
+ dataset[, .SD, .SDcols = setdiff(feature_cols, surv_cols[1:2])]
+ )
> train_y <- survival::Surv(
+ event = (dataset[, get("status")] |>
+ as.character() |>
+ as.integer()),
+ time = dataset[, get("time")],
+ type = "right"
+ )
>
> fold_list <- splitTools::create_folds(
+ y = split_vector,
+ k = 3,
+ type = "stratified",
+ seed = seed
+ )
>
>
> surv_coxph_cox_optimizer <- mlexperiments::MLCrossValidation$new(
+ learner = LearnerSurvCoxPHCox$new(),
+ fold_list = fold_list,
+ ncores = 1L,
+ seed = seed
+ )
> surv_coxph_cox_optimizer$performance_metric <- c_index
>
> # set data
> surv_coxph_cox_optimizer$set_data(
+ x = train_x,
+ y = train_y
+ )
>
> surv_coxph_cox_optimizer$execute()
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Execution halted
Flavor: r-release-windows-x86_64
Version: 0.0.5
Check: tests
Result: ERROR
Running 'testthat.R' [249s]
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(mlsurvlrnrs)
>
> test_check("mlsurvlrnrs")
CV fold: Fold1
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold2
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold3
Parameter 'ncores' is ignored for learner 'LearnerSurvCoxPHCox'.
CV fold: Fold1
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 4.92 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.94 seconds
3) Running FUN 2 times in 2 thread(s)... 0.64 seconds
CV fold: Fold2
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 4.97 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.97 seconds
3) Running FUN 2 times in 2 thread(s)... 0.61 seconds
CV fold: Fold3
Registering parallel backend using 2 cores.
Running initial scoring function 6 times in 2 thread(s)... 4.71 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.59 seconds
3) Running FUN 2 times in 2 thread(s)... 0.64 seconds
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)... 4.06 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters... 6.8 seconds
3) Running FUN 2 times in 2 thread(s)... 0.26 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)... 3.58 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 13.32 seconds
3) Running FUN 2 times in 2 thread(s)... 0.32 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)... 3.79 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search... 0.64 seconds
3) Running FUN 2 times in 2 thread(s)... 0.26 seconds
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)... 3.97 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.42 seconds
3) Running FUN 2 times in 2 thread(s)... 0.29 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)... 3.38 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.41 seconds
3) Running FUN 2 times in 2 thread(s)... 0.27 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)... 3.94 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 0.46 seconds
3) Running FUN 2 times in 2 thread(s)... 0.31 seconds
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)... 4.36 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 11.01 seconds
3) Running FUN 2 times in 2 thread(s)... 0.32 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)... 4.48 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 10.01 seconds
3) Running FUN 2 times in 2 thread(s)... 0.39 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)... 4.74 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 5.75 seconds
3) Running FUN 2 times in 2 thread(s)... 0.43 seconds
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)... 3.7 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
- Could not obtain meaningful lengthscales.
2) Running local optimum search...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters...
- Convergence Not Found. Trying again with tighter parameters...
- Maximum convergence attempts exceeded - process is probably sampling random points. 71.34 seconds
3) Running FUN 2 times in 2 thread(s)... 0.25 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)... 3.42 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 9.38 seconds
3) Running FUN 2 times in 2 thread(s)... 0.26 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)... 3.4 seconds
Starting Epoch 1
1) Fitting Gaussian Process...
2) Running local optimum search... 2.13 seconds
3) Running FUN 2 times in 2 thread(s)... 0.27 seconds
[ FAIL 6 | WARN 0 | SKIP 1 | PASS 0 ]
══ Skipped tests (1) ═══════════════════════════════════════════════════════════
• On CRAN (1): 'test-lints.R:10:5'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-surv_coxph_cox.R:56:5'): test cv - surv_coxph_cox ──────────────
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_coxph_cox_optimizer$execute() at test-surv_coxph_cox.R:56:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_glmnet_cox.R:99:5'): test nested cv, grid - surv_glmnet_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_glmnet_cox_optimizer$execute() at test-surv_glmnet_cox.R:99:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_ranger_cox.R:110:5'): test nested cv, bayesian - surv_ranger_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_ranger_cox_optimizer$execute() at test-surv_ranger_cox.R:110:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_rpart_cox.R:108:5'): test nested cv, bayesian - surv_rpart_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_rpart_cox_optimizer$execute() at test-surv_rpart_cox.R:108:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_xgboost_aft.R:116:5'): test nested cv, bayesian - surv_xgboost_aft ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_xgboost_aft_optimizer$execute() at test-surv_xgboost_aft.R:116:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
── Error ('test-surv_xgboost_cox.R:115:5'): test nested cv, bayesian - surv_xgboost_cox ──
Error: Package "measures" must be installed to use function 'metric_types_helper()'.
Backtrace:
▆
1. └─surv_xgboost_cox_optimizer$execute() at test-surv_xgboost_cox.R:115:5
2. └─mlexperiments:::.run_cv(self = self, private = private)
3. └─mlexperiments:::.cv_postprocessing(...)
4. └─mlexperiments:::.compute_performance(...)
5. └─base::sapply(...)
6. └─base::lapply(X = X, FUN = FUN, ...)
7. └─mlexperiments (local) FUN(X[[i]], ...)
8. └─mlexperiments::metric_types_helper(...)
[ FAIL 6 | WARN 0 | SKIP 1 | PASS 0 ]
Error: Test failures
Execution halted
Flavor: r-release-windows-x86_64