Last updated on 2024-11-03 15:49:02 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.7.8.1 | 463.22 | 269.86 | 733.08 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.7.8.1 | 0.65 | 2.00 | 2.65 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.7.8.1 | 1366.57 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.7.8.1 | 1722.29 | OK | |||
| r-devel-windows-x86_64 | 1.7.8.1 | 566.00 | 291.00 | 857.00 | OK | |
| r-patched-linux-x86_64 | 1.7.8.1 | 578.75 | 281.38 | 860.13 | NOTE | |
| r-release-linux-x86_64 | 1.7.8.1 | 593.38 | 192.63 | 786.01 | ERROR | |
| r-release-macos-arm64 | 1.7.8.1 | 356.00 | NOTE | |||
| r-release-macos-x86_64 | 1.7.8.1 | 689.00 | NOTE | |||
| r-release-windows-x86_64 | 1.7.8.1 | 555.00 | 304.00 | 859.00 | NOTE | |
| r-oldrel-macos-arm64 | 1.7.8.1 | 355.00 | NOTE | |||
| r-oldrel-macos-x86_64 | 1.7.8.1 | 609.00 | NOTE | |||
| r-oldrel-windows-x86_64 | 1.7.8.1 | 650.00 | 407.00 | 1057.00 | NOTE |
Version: 1.7.8.1
Check: whether package can be installed
Result: ERROR
Installation failed.
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.7.8.1
Check: for GNU extensions in Makefiles
Result: NOTE
GNU make is a SystemRequirements.
Flavors: r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 1.7.8.1
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘Ckmeans.1d.dp’
Flavor: r-release-linux-x86_64
Version: 1.7.8.1
Check: examples
Result: ERROR
Running examples in ‘xgboost-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: xgb.ggplot.importance
> ### Title: Plot feature importance as a bar graph
> ### Aliases: xgb.ggplot.importance xgb.plot.importance
>
> ### ** Examples
>
> data(agaricus.train)
> ## Keep the number of threads to 2 for examples
> nthread <- 2
> data.table::setDTthreads(nthread)
>
> bst <- xgboost(
+ data = agaricus.train$data, label = agaricus.train$label, max_depth = 3,
+ eta = 1, nthread = nthread, nrounds = 2, objective = "binary:logistic"
+ )
[1] train-logloss:0.161178
[2] train-logloss:0.064728
>
> importance_matrix <- xgb.importance(colnames(agaricus.train$data), model = bst)
>
> xgb.plot.importance(importance_matrix, rel_to_first = TRUE, xlab = "Relative importance")
>
> (gg <- xgb.ggplot.importance(importance_matrix, measure = "Frequency", rel_to_first = TRUE))
Error: Ckmeans.1d.dp package is required
Execution halted
Flavor: r-release-linux-x86_64
Version: 1.7.8.1
Check: tests
Result: ERROR
Running ‘testthat.R’ [101s/102s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(xgboost)
>
> test_check("xgboost", reporter = ProgressReporter)
✔ | F W S OK | Context
⠏ | 0 | basic
⠏ | 0 | basic functions
⠋ | 1 | basic functions
⠦ | 7 | basic functions [17:00:13] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[1] train-rmse:1.678965
[2] train-rmse:1.678965
[3] train-rmse:1.524624
[4] train-rmse:1.441523
[5] train-rmse:1.437758
[6] train-rmse:1.377895
[7] train-rmse:1.305894
[8] train-rmse:1.336120
[9] train-rmse:1.316072
[10] train-rmse:1.316031
[11] train-rmse:1.319404
[12] train-rmse:1.235097
[13] train-rmse:1.225430
[14] train-rmse:1.221079
[15] train-rmse:1.235220
[16] train-rmse:1.219153
[17] train-rmse:1.226439
[18] train-rmse:1.235026
[19] train-rmse:1.244651
[20] train-rmse:1.253197
[21] train-rmse:1.262494
[22] train-rmse:1.272865
[23] train-rmse:1.276073
[24] train-rmse:1.277040
[25] train-rmse:1.287974
[26] train-rmse:1.289816
[27] train-rmse:1.292365
[28] train-rmse:1.282785
[29] train-rmse:1.283805
[30] train-rmse:1.290661
[31] train-rmse:1.289439
[32] train-rmse:1.281995
[17:00:14] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
⠼ | 15 | basic functions [17:00:14] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
⠹ | 23 | basic functions [17:00:14] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
⠇ | 29 | basic functions [1] train-error:0.028405
⠦ | 37 | basic functions [17:00:14] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
⠋ | 41 | basic functions [17:00:14] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
⠦ | 47 | basic functions
⠼ | 55 | basic functions [1] train-logloss:0.439409
[2] train-logloss:0.299260
[3] train-logloss:0.209937
[4] train-logloss:0.150151
⠏ | 60 | basic functions [1] train-logloss:0.233470+0.001565 test-logloss:0.233607+0.004930
[2] train-logloss:0.136851+0.001767 test-logloss:0.137010+0.006645
[1] train-logloss:0.233482+0.001761 test-logloss:0.233527+0.005591
[2] train-logloss:0.136860+0.002158 test-logloss:0.136933+0.007299
⠋ | 71 | basic functions
⠙ | 72 | basic functions
⠹ | 73 | basic functions
⠦ | 77 | basic functions
⠋ | 81 | basic functions [1] train-logloss:0.380598
[2] train-logloss:0.247331
[3] train-logloss:0.175047
[4] train-logloss:0.122301
[5] train-logloss:0.089889
[1] train-logloss:0.497338
[2] train-logloss:0.357306
[3] train-logloss:0.257215
[4] train-logloss:0.184518
[5] train-logloss:0.132113
⠙ | 82 | basic functions [1] train-error:0.046522 train-auc:0.958228 train-logloss:0.233376
[2] train-error:0.022263 train-auc:0.981413 train-logloss:0.136658
⠼ | 85 | basic functions [1] train-merror:0.040000
[2] train-merror:0.026667
[1] train-error:0.046522 train-auc:0.958228 train-logloss:0.482541
[2] train-error:0.046522 train-auc:0.987161 train-logloss:0.359536
⠸ | 94 | basic functions
⠇ | 99 | basic functions
✔ | 100 | basic functions [8.7s]
⠏ | 0 | callbacks
⠏ | 0 | callbacks [1] train-auc:0.900000 test-auc:0.800000
⠙ | 12 | callbacks
⠴ | 26 | callbacks
⠙ | 32 | callbacks
⠧ | 38 | callbacks
⠏ | 40 | callbacks
⠇ | 1 48 | callbacks
⠙ | 1 51 | callbacks
⠧ | 1 57 | callbacks
⠹ | 1 62 | callbacks [17:00:24] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[1] train-auc:0.829749
Will train until train_auc hasn't improved in 3 rounds.
[2] train-auc:0.829749
[3] train-auc:0.829749
[4] train-auc:0.829749
Stopping. Best iteration:
[1] train-auc:0.829749
⠏ | 1 69 | callbacks
⠼ | 1 74 | callbacks
⠇ | 1 78 | callbacks
⠙ | 1 81 | callbacks
⠼ | 1 84 | callbacks
⠹ | 1 92 | callbacks
✔ | 1 95 | callbacks [4.4s]
────────────────────────────────────────────────────────────────────────────────
Warning ('test_callbacks.R:200:3'): cb.save.model works as expected
one argument not used by format 'xgboost.json'
Backtrace:
▆
1. └─xgboost::xgb.train(...) at test_callbacks.R:200:3
2. └─xgboost (local) f()
3. ├─xgboost::xgb.save(env$bst, sprintf(save_name, env$iteration))
4. └─base::sprintf(save_name, env$iteration)
────────────────────────────────────────────────────────────────────────────────
⠏ | 0 | config
⠏ | 0 | Test global configuration
✔ | 8 | Test global configuration
⠏ | 0 | custom_objective
⠏ | 0 | Test models with custom objective [1] eval-error:0.042831 train-error:0.046522
[2] eval-error:0.021726 train-error:0.022263
⠋ | 1 | Test models with custom objective
⠼ | 5 | Test models with custom objective [1] eval-error:0.042831 train-error:0.046522
[2] eval-error:0.021726 train-error:0.022263
[3] eval-error:0.018001 train-error:0.015200
[4] eval-error:0.018001 train-error:0.015200
[5] eval-error:0.006207 train-error:0.007063
[6] eval-error:0.000000 train-error:0.001228
[7] eval-error:0.000000 train-error:0.001228
[8] eval-error:0.000000 train-error:0.001228
[9] eval-error:0.000000 train-error:0.001228
[10] eval-error:0.000000 train-error:0.000000
⠧ | 8 | Test models with custom objective [1] eval-error:0.042831 train-error:0.046522
[2] eval-error:0.021726 train-error:0.022263
⠏ | 10 | Test models with custom objective
✔ | 12 | Test models with custom objective [1.2s]
⠏ | 0 | dmatrix
⠏ | 0 | testing xgb.DMatrix functionality
⠧ | 8 | testing xgb.DMatrix functionality
⠸ | 14 | testing xgb.DMatrix functionality [17:00:28] 6513x126 matrix with 143286 entries loaded from /home/hornik/tmp/scratch/RtmpYvBzQY/xgb.DMatrix_25c9de9439f
⠋ | 1 30 | testing xgb.DMatrix functionality
⠦ | 1 36 | testing xgb.DMatrix functionality
⠇ | 1 38 | testing xgb.DMatrix functionality
✔ | 1 44 | testing xgb.DMatrix functionality
────────────────────────────────────────────────────────────────────────────────
Warning ('test_dmatrix.R:125:3'): xgb.DMatrix: getinfo & setinfo
NAs introduced by coercion
Backtrace:
▆
1. ├─testthat::expect_error(setinfo(dtest, "weight", rep("a", nrow(test_data)))) at test_dmatrix.R:125:3
2. │ └─testthat:::quasi_capture(...)
3. │ ├─testthat (local) .capture(...)
4. │ │ └─base::withCallingHandlers(...)
5. │ └─rlang::eval_bare(quo_get_expr(.quo), quo_get_env(.quo))
6. ├─xgboost::setinfo(dtest, "weight", rep("a", nrow(test_data)))
7. └─xgboost:::setinfo.xgb.DMatrix(dtest, "weight", rep("a", nrow(test_data)))
────────────────────────────────────────────────────────────────────────────────
⠏ | 0 | feature_weights
⠏ | 0 | feature weights
⠙ | 2 | feature weights
⠹ | 3 | feature weights
⠴ | 6 | feature weights
✔ | 6 | feature weights
⠏ | 0 | gc_safety
⠏ | 0 | Garbage Collection Safety Check [1] train-logloss:0.233376
[2] train-logloss:0.136658
⠋ | 1 | Garbage Collection Safety Check
✔ | 1 | Garbage Collection Safety Check [72.4s]
⠏ | 0 | glm
⠏ | 0 | Test generalized linear models
⠦ | 7 | Test generalized linear models [1] eval-error:0.002483 train-error:0.004760
Multiple eval metrics are present. Will use train_error for early stopping.
Will train until train_error hasn't improved in 1 rounds.
[2] eval-error:0.000621 train-error:0.002610
[3] eval-error:0.000000 train-error:0.001842
[4] eval-error:0.000000 train-error:0.001228
[5] eval-error:0.000000 train-error:0.000614
[6] eval-error:0.000000 train-error:0.000614
Stopping. Best iteration:
[5] eval-error:0.000000 train-error:0.000614
⠙ | 12 | Test generalized linear models [1] eval-error:0.002483 train-error:0.004760
Multiple eval metrics are present. Will use train_error for early stopping.
Will train until train_error hasn't improved in 1 rounds.
[2] eval-error:0.000621 train-error:0.002610
[3] eval-error:0.000000 train-error:0.001842
[4] eval-error:0.000000 train-error:0.001228
[5] eval-error:0.000000 train-error:0.000614
[6] eval-error:0.000000 train-error:0.000614
Stopping. Best iteration:
[5] eval-error:0.000000 train-error:0.000614
✔ | 13 | Test generalized linear models
⠏ | 0 | helpers
⠏ | 0 | Test helper functions
⠋ | 1 | Test helper functions [1] train-logloss:0.636592
⠴ | 36 | Test helper functions [1] train-rmse:1.940066
[2] train-rmse:1.560864
[3] train-rmse:1.277414
[4] train-rmse:1.068562
[5] train-rmse:0.903897
[6] train-rmse:0.763228
[7] train-rmse:0.664924
[8] train-rmse:0.570358
[9] train-rmse:0.507416
[10] train-rmse:0.458599
[11] train-rmse:0.394349
[12] train-rmse:0.355794
[13] train-rmse:0.305484
[14] train-rmse:0.271176
[15] train-rmse:0.259943
[16] train-rmse:0.238429
[17] train-rmse:0.228003
[18] train-rmse:0.212117
[19] train-rmse:0.187830
[20] train-rmse:0.173381
[21] train-rmse:0.164001
[22] train-rmse:0.156113
[23] train-rmse:0.143242
[24] train-rmse:0.130215
[25] train-rmse:0.120160
[26] train-rmse:0.112119
[27] train-rmse:0.104753
[28] train-rmse:0.096786
[29] train-rmse:0.089361
[30] train-rmse:0.083706
⠦ | 67 | Test helper functions
⠧ | 148 | Test helper functions
⠧ | 228 | Test helper functions [1] train-rmse:1.940066
[2] train-rmse:1.675038
[3] train-rmse:1.462383
[4] train-rmse:1.283198
[5] train-rmse:1.155542
[6] train-rmse:1.049559
[7] train-rmse:0.942910
[8] train-rmse:0.859371
[9] train-rmse:0.774970
[10] train-rmse:0.725452
[11] train-rmse:0.679127
[12] train-rmse:0.628614
[13] train-rmse:0.594549
[14] train-rmse:0.535545
[15] train-rmse:0.485623
[16] train-rmse:0.460187
[17] train-rmse:0.413632
[18] train-rmse:0.403692
[19] train-rmse:0.385314
[20] train-rmse:0.366653
[21] train-rmse:0.354532
[22] train-rmse:0.326526
[23] train-rmse:0.316875
[24] train-rmse:0.301910
[25] train-rmse:0.285458
[26] train-rmse:0.275437
[27] train-rmse:0.267556
[28] train-rmse:0.263727
[29] train-rmse:0.253460
[30] train-rmse:0.235433
⠴ | 266 | Test helper functions
⠧ | 348 | Test helper functions
⠋ | 431 | Test helper functions
⠇ | 489 | Test helper functions
⠴ | 556 | Test helper functions
⠴ | 626 | Test helper functions
⠙ | 672 | Test helper functions
⠼ | 685 | Test helper functions
⠴ | 1 685 | Test helper functions
⠴ | 2 694 | Test helper functions
⠦ | 2 695 | Test helper functions
⠧ | 2 1 695 | Test helper functions
⠏ | 2 1 697 | Test helper functions
⠴ | 2 1 713 | Test helper functions
✖ | 2 1 743 | Test helper functions [3.2s]
────────────────────────────────────────────────────────────────────────────────
Error ('test_helpers.R:310:3'): xgb.importance works with and without feature names
Error: Ckmeans.1d.dp package is required
Backtrace:
▆
1. └─xgboost::xgb.ggplot.importance(importance_matrix = importance.Tree) at test_helpers.R:310:3
Error ('test_helpers.R:364:3'): xgb.importance works with GLM model
Error: Ckmeans.1d.dp package is required
Backtrace:
▆
1. └─xgboost::xgb.ggplot.importance(importance.GLM) at test_helpers.R:364:3
────────────────────────────────────────────────────────────────────────────────
⠏ | 0 | interaction_constraints
⠏ | 0 | interaction constraints
⠙ | 2 | interaction constraints
✔ | 2 | interaction constraints [4.2s]
⠏ | 0 | interactions
⠏ | 0 | Test prediction of feature interactions
⠸ | 4 | Test prediction of feature interactions
⠦ | 17 | Test prediction of feature interactions [1] train-logloss:0.482541
[2] train-logloss:0.359536
[3] train-logloss:0.279935
[4] train-logloss:0.218599
✔ | 19 | Test prediction of feature interactions
⠏ | 0 | io
⠏ | 0 | Test model IO. [1] train-logloss:0.439409
[2] train-logloss:0.299260
[3] train-logloss:0.209937
[4] train-logloss:0.150151
[5] train-logloss:0.108673
[6] train-logloss:0.079348
[7] train-logloss:0.058385
[8] train-logloss:0.043147
✔ | 2 | Test model IO.
⠏ | 0 | model_compatibility
⠏ | 0 | Models from previous versions of XGBoost can be loaded
⠋ | 1 | Models from previous versions of XGBoost can be loaded
⠙ | 12 | Models from previous versions of XGBoost can be loaded
⠹ | 63 | Models from previous versions of XGBoost can be loaded
⠹ | 113 | Models from previous versions of XGBoost can be loaded
⠹ | 163 | Models from previous versions of XGBoost can be loaded
⠧ | 208 | Models from previous versions of XGBoost can be loaded
✔ | 233 | Models from previous versions of XGBoost can be loaded [1.5s]
⠏ | 0 | monotone
⠏ | 0 | monotone constraints
✔ | 1 | monotone constraints
⠏ | 0 | parameter_exposure
⠏ | 0 | Test model params and call are exposed to R
✔ | 6 | Test model params and call are exposed to R
⠏ | 0 | poisson_regression
⠏ | 0 | Test Poisson regression model
✔ | 3 | Test Poisson regression model
⠏ | 0 | ranking
⠏ | 0 | Learning to rank [1] train-auc:0.575000 train-aucpr:0.550000
[2] train-auc:0.650000 train-aucpr:0.700000
[3] train-auc:0.725000 train-aucpr:0.850000
[4] train-auc:0.800000 train-aucpr:1.000000
[5] train-auc:0.800000 train-aucpr:1.000000
[6] train-auc:0.800000 train-aucpr:1.000000
[7] train-auc:0.800000 train-aucpr:1.000000
[8] train-auc:0.800000 train-aucpr:1.000000
[9] train-auc:0.800000 train-aucpr:1.000000
[10] train-auc:0.800000 train-aucpr:1.000000
[1] train-auc:0.575000 train-aucpr:0.550000
[2] train-auc:0.650000 train-aucpr:0.700000
[3] train-auc:0.725000 train-aucpr:0.850000
[4] train-auc:0.725000 train-aucpr:0.850000
[5] train-auc:0.725000 train-aucpr:0.850000
[6] train-auc:0.725000 train-aucpr:0.850000
[7] train-auc:0.725000 train-aucpr:0.850000
[8] train-auc:0.800000 train-aucpr:1.000000
[9] train-auc:0.800000 train-aucpr:1.000000
[10] train-auc:0.800000 train-aucpr:1.000000
[17:01:51] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[17:01:51] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[17:01:51] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[17:01:51] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[17:01:51] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[17:01:52] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[17:01:52] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[17:01:52] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[17:01:52] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
[17:01:52] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
✔ | 14 | Learning to rank
⠏ | 0 | unicode
⠏ | 0 | Test Unicode handling [1] train-error:0.046522
[2] train-error:0.022263
✔ | 3 | Test Unicode handling
⠏ | 0 | update
⠏ | 0 | update trees in an existing model [17:01:52] WARNING: src/gbm/gbtree.cc:84: DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.
[17:01:52] WARNING: src/gbm/gbtree.cc:84: DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.
[17:01:52] WARNING: src/gbm/gbtree.cc:84: DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.
⠋ | 1 | update trees in an existing model [17:01:52] WARNING: src/gbm/gbtree.cc:84: DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.
[17:01:52] WARNING: src/gbm/gbtree.cc:84: DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.
[17:01:52] WARNING: src/gbm/gbtree.cc:84: DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.
⠇ | 9 | update trees in an existing model [17:01:52] WARNING: src/gbm/gbtree.cc:84: DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.
[17:01:52] WARNING: src/gbm/gbtree.cc:84: DANGER AHEAD: You have manually specified `updater` parameter. The `tree_method` parameter will be ignored. Incorrect sequence of updaters will produce undefined behavior. For common uses, we recommend using `tree_method` parameter instead.
✔ | 22 | update trees in an existing model
══ Results ═════════════════════════════════════════════════════════════════════
Duration: 98.8 s
── Skipped tests (1) ───────────────────────────────────────────────────────────
• empty test (1): 'test_helpers.R:388:1'
── Failed tests ────────────────────────────────────────────────────────────────
Error ('test_helpers.R:310:3'): xgb.importance works with and without feature names
Error: Ckmeans.1d.dp package is required
Backtrace:
▆
1. └─xgboost::xgb.ggplot.importance(importance_matrix = importance.Tree) at test_helpers.R:310:3
Error ('test_helpers.R:364:3'): xgb.importance works with GLM model
Error: Ckmeans.1d.dp package is required
Backtrace:
▆
1. └─xgboost::xgb.ggplot.importance(importance.GLM) at test_helpers.R:364:3
[ FAIL 2 | WARN 2 | SKIP 1 | PASS 1327 ]
Error: Test failures
Execution halted
Flavor: r-release-linux-x86_64
Version: 1.7.8.1
Check: HTML version of manual
Result: NOTE
Skipping checking math rendering: package 'V8' unavailable
Flavor: r-release-linux-x86_64
Version: 1.7.8.1
Check: installed package size
Result: NOTE
installed size is 54.1Mb
sub-directories of 1Mb or more:
libs 53.2Mb
Flavors: r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64