R Under development (unstable) (2023-07-09 r84667 ucrt) -- "Unsuffered Consequences" Copyright (C) 2023 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # 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(mllrnrs) > > test_check("mllrnrs") 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)... 2.5 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.32 seconds 3) Running FUN 2 times in 2 thread(s)... 0.21 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)... 2.75 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.4 seconds 3) Running FUN 2 times in 2 thread(s)... 0.22 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)... 2.46 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.31 seconds 3) Running FUN 2 times in 2 thread(s)... 0.2 seconds CV fold: Fold1 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)... 5.91 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.38 seconds 3) Running FUN 2 times in 2 thread(s)... 0.78 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)... 6.2 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.71 seconds 3) Running FUN 2 times in 2 thread(s)... 1.11 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)... 6.14 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.79 seconds 3) Running FUN 2 times in 2 thread(s)... 0.81 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)... 2.72 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.28 seconds 3) Running FUN 2 times in 2 thread(s)... 0.2 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)... 2.33 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.28 seconds 3) Running FUN 2 times in 2 thread(s)... 0.17 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)... 2.42 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.29 seconds 3) Running FUN 2 times in 2 thread(s)... 0.19 seconds CV fold: Fold1 CV fold: Fold2 CV fold: Fold3 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)... 2.7 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 3.03 seconds 3) Running FUN 2 times in 2 thread(s)... 0.27 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 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 5.34 seconds 3) Running FUN 2 times in 2 thread(s)... 0.22 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)... 2.98 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 12.25 seconds 3) Running FUN 2 times in 2 thread(s)... 0.22 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)... 3.59 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 5.6 seconds 3) Running FUN 2 times in 2 thread(s)... 0.88 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)... 3.25 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 4.43 seconds 3) Running FUN 2 times in 2 thread(s)... 0.72 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)... 3.92 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 5.41 seconds 3) Running FUN 2 times in 2 thread(s)... 0.8 seconds CV fold: Fold1 Registering parallel backend using 2 cores. Running initial scoring function 10 times in 2 thread(s)... 3.1 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 4.95 seconds 3) Running FUN 2 times in 2 thread(s)... 0.26 seconds CV fold: Fold2 Registering parallel backend using 2 cores. Running initial scoring function 10 times in 2 thread(s)... 3.14 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 6.94 seconds 3) Running FUN 2 times in 2 thread(s)... 0.27 seconds CV fold: Fold3 Registering parallel backend using 2 cores. Running initial scoring function 10 times in 2 thread(s)... 3.09 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 7.41 seconds 3) Running FUN 2 times in 2 thread(s)... 0.31 seconds CV fold: Fold1 [LightGBM] [Info] Start training from score 22.606222 [LightGBM] [Info] Start training from score 22.555507 [LightGBM] [Info] Start training from score 22.682589 [LightGBM] [Info] Start training from score 22.606222 [LightGBM] [Info] Start training from score 22.555507 [LightGBM] [Info] Start training from score 22.682589 [LightGBM] [Info] Start training from score 22.606222 [LightGBM] [Info] Start training from score 22.555507 [LightGBM] [Info] Start training from score 22.682589 CV fold: Fold2 [LightGBM] [Info] Start training from score 22.530089 [LightGBM] [Info] Start training from score 22.396460 [LightGBM] [Info] Start training from score 22.310620 [LightGBM] [Info] Start training from score 22.530089 [LightGBM] [Info] Start training from score 22.396460 [LightGBM] [Info] Start training from score 22.310620 [LightGBM] [Info] Start training from score 22.530089 [LightGBM] [Info] Start training from score 22.396460 [LightGBM] [Info] Start training from score 22.310620 CV fold: Fold3 [LightGBM] [Info] Start training from score 22.675556 [LightGBM] [Info] Start training from score 22.438739 [LightGBM] [Info] Start training from score 22.600897 [LightGBM] [Info] Start training from score 22.675556 [LightGBM] [Info] Start training from score 22.438739 [LightGBM] [Info] Start training from score 22.600897 [LightGBM] [Info] Start training from score 22.675556 [LightGBM] [Info] Start training from score 22.438739 [LightGBM] [Info] Start training from score 22.600897 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)... 3.78 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 2.04 seconds 3) Running FUN 2 times in 2 thread(s)... 0.36 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)... 3.8 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 4.77 seconds 3) Running FUN 2 times in 2 thread(s)... 0.22 seconds Errors encountered in FUN 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)... 3.64 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 3.07 seconds 3) Running FUN 2 times in 2 thread(s)... 0.45 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)... 6.82 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 5.22 seconds 3) Running FUN 2 times in 2 thread(s)... 1.01 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)... 6.47 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 1.67 seconds 3) Running FUN 2 times in 2 thread(s)... 0.47 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)... 6.69 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 1.47 seconds 3) Running FUN 2 times in 2 thread(s)... 0.7 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)... 3.33 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.63 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)... 3.43 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.61 seconds 3) Running FUN 2 times in 2 thread(s)... 0.31 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)... 3.35 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 0.73 seconds 3) Running FUN 2 times in 2 thread(s)... 0.3 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. 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)... 2.58 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 4.38 seconds 3) Running FUN 2 times in 2 thread(s)... 0.23 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)... 2.67 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 3.46 seconds 3) Running FUN 2 times in 2 thread(s)... 0.19 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)... 2.66 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 5.89 seconds 3) Running FUN 2 times in 2 thread(s)... 0.3 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)... 5.8 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 1.44 seconds 3) Running FUN 2 times in 2 thread(s)... 1.29 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)... 5.15 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 7.03 seconds 3) Running FUN 2 times in 2 thread(s)... 0.87 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)... 5.8 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 6.18 seconds 3) Running FUN 2 times in 2 thread(s)... 1.37 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)... 3.13 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 12.11 seconds 3) Running FUN 2 times in 2 thread(s)... 0.38 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)... 2.9 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 1.6 seconds 3) Running FUN 2 times in 2 thread(s)... 0.28 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)... 2.94 seconds Starting Epoch 1 1) Fitting Gaussian Process... 2) Running local optimum search... 6.19 seconds 3) Running FUN 2 times in 2 thread(s)... 0.33 seconds CV fold: Fold1 CV fold: Fold2 CV fold: Fold3 [ FAIL 0 | WARN 0 | SKIP 1 | PASS 49 ] ══ Skipped tests (1) ═══════════════════════════════════════════════════════════ • On CRAN (1): 'test-lints.R:10:5' [ FAIL 0 | WARN 0 | SKIP 1 | PASS 49 ] > > proc.time() user system elapsed 41.07 2.56 341.31