• using R Under development (unstable) (2026-01-12 r89299)
• using platform: x86_64-pc-linux-gnu
• R was compiled by     gcc (GCC) 15.1.1 20250521 (Red Hat 15.1.1-2)     GNU Fortran (GCC) 15.1.1 20250521 (Red Hat 15.1.1-2)
• running under: Fedora Linux 42 (Workstation Edition)
• using session charset: UTF-8
• using option ‘--no-stop-on-test-error’
• checking for file ‘mllrnrs/DESCRIPTION’ ... OK
• this is package ‘mllrnrs’ version ‘0.0.7’
• package encoding: UTF-8
• checking package namespace information ... OK
• checking package dependencies ... INFO Package suggested but not available for checking: ‘ParBayesianOptimization’
• checking if this is a source package ... OK
• checking if there is a namespace ... OK
• checking for executable files ... OK
• checking for hidden files and directories ... OK
• checking for portable file names ... OK
• checking for sufficient/correct file permissions ... OK
• checking whether package ‘mllrnrs’ can be installed ... [9s/11s] OK See the install log for details.
• checking package directory ... OK
• checking ‘build’ directory ... OK
• checking DESCRIPTION meta-information ... OK
• checking top-level files ... OK
• checking for left-over files ... OK
• checking index information ... OK
• checking package subdirectories ... OK
• checking code files for non-ASCII characters ... OK
• checking R files for syntax errors ... OK
• checking whether the package can be loaded ... OK
• checking whether the package can be loaded with stated dependencies ... OK
• checking whether the package can be unloaded cleanly ... OK
• checking whether the namespace can be loaded with stated dependencies ... OK
• checking whether the namespace can be unloaded cleanly ... OK
• checking loading without being on the library search path ... OK
• checking whether startup messages can be suppressed ... OK
• checking use of S3 registration ... OK
• checking dependencies in R code ... OK
• checking S3 generic/method consistency ... OK
• checking replacement functions ... OK
• checking foreign function calls ... OK
• checking R code for possible problems ... OK
• checking Rd files ... OK
• checking Rd metadata ... OK
• checking Rd line widths ... OK
• checking Rd cross-references ... OK
• checking for missing documentation entries ... OK
• checking for code/documentation mismatches ... OK
• checking Rd \usage sections ... OK
• checking Rd contents ... OK
• checking for unstated dependencies in examples ... OK
• checking installed files from ‘inst/doc’ ... OK
• checking files in ‘vignettes’ ... OK
• checking examples ... OK
• checking for unstated dependencies in ‘tests’ ... OK
• checking tests ... [113s/117s] ERROR   Running ‘testthat.R’ [112s/117s] 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   > # https://github.com/Rdatatable/data.table/issues/5658   > Sys.setenv("OMP_THREAD_LIMIT" = 2)   > Sys.setenv("Ncpu" = 2)   >   > library(testthat)   > library(mllrnrs)   >   > test_check("mllrnrs")      CV fold: Fold1      CV fold: Fold1      Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...   ... reducing initialization grid to 10 rows.   Saving _problems/test-binary-225.R      CV fold: Fold1       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.      CV fold: Fold2       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.      CV fold: Fold3       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.      CV fold: Fold1      CV fold: Fold2      CV fold: Fold3      CV fold: Fold1      CV fold: Fold2      CV fold: Fold3      CV fold: Fold1       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.      CV fold: Fold2       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.      CV fold: Fold3       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.       Classification: using 'mean classification error' as optimization metric.      CV fold: Fold1      CV fold: Fold2      CV fold: Fold3      CV fold: Fold1   Saving _problems/test-regression-107.R      CV fold: Fold1      CV fold: Fold2      CV fold: Fold3      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.      CV fold: Fold1      Number of rows of initialization grid > than 'options("mlexperiments.bayesian.max_init")'...   ... reducing initialization grid to 10 rows.   Saving _problems/test-regression-309.R      CV fold: Fold1      CV fold: Fold2      CV fold: Fold3   [ FAIL 3 | WARN 0 | SKIP 3 | PASS 25 ]      ══ Skipped tests (3) ═══════════════════════════════════════════════════════════   • On CRAN (3): 'test-binary.R:57:5', 'test-lints.R:10:5',     'test-multiclass.R:57:5'      ══ Failed tests ════════════════════════════════════════════════════════════════   ── Error ('test-binary.R:225:5'): test nested cv, bayesian, binary - lightgbm ──   Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.   Backtrace:        ▆     1. └─lightgbm_optimizer$execute() at test-binary.R:225:5     2. └─mlexperiments:::.run_cv(self = self, private = private)     3. └─mlexperiments:::.fold_looper(self, private)     4. ├─base::do.call(private$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-regression.R:107:5'): test nested cv, bayesian, regression - glmnet ──   Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.   Backtrace:        ▆     1. └─glmnet_optimizer$execute() at test-regression.R:107:5     2. └─mlexperiments:::.run_cv(self = self, private = private)     3. └─mlexperiments:::.fold_looper(self, private)     4. ├─base::do.call(private$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-regression.R:309:5'): test nested cv, bayesian, reg:squarederror - xgboost ──   Error: Package "ParBayesianOptimization" must be installed to use 'strategy = "bayesian"'.   Backtrace:        ▆     1. └─xgboost_optimizer$execute() at test-regression.R:309:5     2. └─mlexperiments:::.run_cv(self = self, private = private)     3. └─mlexperiments:::.fold_looper(self, private)     4. ├─base::do.call(private$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 3 | WARN 0 | SKIP 3 | PASS 25 ]   Error:   ! Test failures.   Execution halted
• checking for unstated dependencies in vignettes ... OK
• checking package vignettes ... OK
• checking re-building of vignette outputs ... [144s/184s] OK
• checking PDF version of manual ... OK
• checking HTML version of manual ... OK
• checking for non-standard things in the check directory ... OK
• checking for detritus in the temp directory ... OK
• DONE

Status: 1 ERROR