CRAN Package Check Results for Package xgboost

Last updated on 2023-03-29 21:55:51 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.7.3.1 598.39 350.86 949.25 NOTE
r-devel-linux-x86_64-debian-gcc 1.7.3.1 592.33 267.32 859.65 NOTE
r-devel-linux-x86_64-fedora-clang 1.7.3.1 1309.28 NOTE
r-devel-linux-x86_64-fedora-gcc 1.7.3.1 1359.74 NOTE
r-patched-linux-x86_64 1.7.3.1 632.22 330.03 962.25 NOTE
r-release-linux-x86_64 1.7.3.1 612.96 312.58 925.54 NOTE
r-release-macos-arm64 1.7.3.1 274.00 NOTE
r-release-macos-x86_64 1.7.3.1 415.00 NOTE
r-release-windows-x86_64 1.7.3.1 722.00 400.00 1122.00 NOTE
r-oldrel-macos-arm64 1.7.3.1 258.00 NOTE
r-oldrel-macos-x86_64 1.7.3.1 405.00 NOTE
r-oldrel-windows-ix86+x86_64 1.7.3.1 1453.00 541.00 1994.00 ERROR

Check Details

Version: 1.7.3.1
Check: C++ specification
Result: NOTE
     Specified C++14: please drop specification unless essential
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64

Version: 1.7.3.1
Check: for GNU extensions in Makefiles
Result: NOTE
    GNU make is a SystemRequirements.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, 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-ix86+x86_64

Version: 1.7.3.1
Check: installed package size
Result: NOTE
     installed size is 5.6Mb
     sub-directories of 1Mb or more:
     libs 4.7Mb
Flavors: r-devel-linux-x86_64-fedora-clang, 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-ix86+x86_64

Version: 1.7.3.1
Check: whether package can be installed
Result: WARN
    Found the following significant warnings:
     src/predictor/cpu_predictor.cc:167:27: warning: narrowing conversion of '(long long unsigned int)beg' from 'long long unsigned int' to 'size_t' {aka 'unsigned int'} inside { } [-Wnarrowing]
Flavor: r-oldrel-windows-ix86+x86_64

Version: 1.7.3.1
Check: running examples for arch ‘i386’
Result: ERROR
    Running examples in 'xgboost-Ex.R' failed
    The error most likely occurred in:
    
    > ### Name: xgb.set.config, xgb.get.config
    > ### Title: Set and get global configuration
    > ### Aliases: 'xgb.set.config, xgb.get.config' xgb.set.config xgb.get.config
    >
    > ### ** Examples
    >
    > # Set verbosity level to silent (0)
    > xgb.set.config(verbosity = 0)
    [1] TRUE
    > # Now global verbosity level is 0
    > config <- xgb.get.config()
    > print(config$verbosity)
    [1] 0
    > # Set verbosity level to warning (1)
    > xgb.set.config(verbosity = 1)
    [1] TRUE
    > # Now global verbosity level is 1
    > config <- xgb.get.config()
    > print(config$verbosity)
    [1] 1
    >
    >
    >
    > ### * <FOOTER>
    > ###
    > cleanEx()
    > options(digits = 7L)
    > base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
    Time elapsed: 23.74 1.29 23.37 NA NA
    > grDevices::dev.off()
    null device
     1
    > ###
    > ### Local variables: ***
    > ### mode: outline-minor ***
    > ### outline-regexp: "\\(> \\)?### [*]+" ***
    > ### End: ***
    > quit('no')
Flavor: r-oldrel-windows-ix86+x86_64

Version: 1.7.3.1
Check: running tests for arch ‘i386’
Result: ERROR
     Running 'testthat.R' [131s]
    Running the tests in 'tests/testthat.R' failed.
    Complete output:
     > library(testthat)
     > library(xgboost)
     >
     > test_check("xgboost", reporter = ProgressReporter)
     v | F W S OK | Context
    
     / | 0 | basic
     / | 0 | basic functions
     - | 1 | basic functions
     / | 4 | basic functions [20:31:31] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
    
     \ | 10 | basic functions [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
     [20:31:32] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
    
     \ | 14 | basic functions [20:31:32] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
    
     | | 19 | basic functions [20:31:32] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
    
     - | 29 | basic functions [1] train-error:0.027944
    
     - | 37 | basic functions [20:31:32] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
    
     \ | 42 | basic functions [20:31:32] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
    
     | | 47 | basic functions
     | | 51 | basic functions [1] train-logloss:0.439409
     [2] train-logloss:0.299260
     [3] train-logloss:0.209937
     [4] train-logloss:0.150151
    
     / | 56 | basic functions
     - | 57 | 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
    
     / | 68 | basic functions
     - | 69 | basic functions
     \ | 70 | basic functions
     \ | 74 | 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
    
     | | 79 | basic functions
     - | 81 | 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
     [1] train-merror:0.040000
     [2] train-merror:0.026667
    
     | | 87 | basic functions [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
    
     | | 91 | basic functions
     / | 96 | basic functions
     v | 97 | basic functions [9.9s]
    
     / | 0 | callbacks
     / | 0 | callbacks
     - | 1 | callbacks [1] train-auc:0.900000 test-auc:0.800000
    
     \ | 26 | callbacks
     \ | 34 | callbacks
     | | 39 | callbacks
     - | 1 48 | callbacks
     - | 1 52 | callbacks
     / | 1 59 | callbacks
     \ | 1 65 | callbacks [20:31:42] 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
     v | 1 95 | callbacks [2.8s]
     --------------------------------------------------------------------------------
     Warning ('test_callbacks.R:196:3'): cb.save.model works as expected
     one argument not used by format 'xgboost.json'
     Backtrace:
     1. xgboost::xgb.train(...)
     at test_callbacks.R:196:2
     2. xgboost (local) f()
     4. base::sprintf(save_name, env$iteration)
     --------------------------------------------------------------------------------
    
     / | 0 | config
     / | 0 | Test global configuration
     v | 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
    
     v | 12 | Test models with custom objective [0.8s]
    
     / | 0 | dmatrix
     / | 0 | testing xgb.DMatrix functionality
     \ | 10 | testing xgb.DMatrix functionality [20:31:45] 6513x126 matrix with 143286 entries loaded from D:\temp\Rtmp44FRZ8\xgb.DMatrix_d29cf654bda
    
     - | 1 24 | testing xgb.DMatrix functionality
     | | 1 26 | testing xgb.DMatrix functionality
     - | 1 32 | testing xgb.DMatrix functionality
     | | 1 34 | testing xgb.DMatrix functionality
     v | 1 40 | testing xgb.DMatrix functionality [1.1s]
     --------------------------------------------------------------------------------
     Warning ('test_dmatrix.R:82:3'): 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:82:2
     7. xgboost:::setinfo.xgb.DMatrix(dtest, "weight", rep("a", nrow(test_data)))
     --------------------------------------------------------------------------------
    
     / | 0 | feature_weights
     / | 0 | feature weights
     - | 1 | feature weights
     | | 3 | feature weights
     - | 5 | feature weights
     v | 6 | feature weights [0.5s]
    
     / | 0 | gc_safety
     / | 0 | Garbage Collection Safety Check [1] train-logloss:0.233376
     [2] train-logloss:0.136658
    
     - | 1 | Garbage Collection Safety Check
     v | 1 | Garbage Collection Safety Check [85.5s]
    
     / | 0 | glm
     / | 0 | Test generalized linear models
     - | 1 | Test generalized linear models
     \ | 6 | Test generalized linear models
     | | 7 | Test generalized linear models
     / | 8 | Test generalized linear models
     - | 9 | 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
     v | 13 | Test generalized linear models [1.2s]
    
     / | 0 | helpers
     / | 0 | Test helper functions
     - | 1 | Test helper functions [1] train-logloss:0.636592
    
     / | 20 | Test helper functions
     \ | 38 | 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
    
     \ | 46 | Test helper functions
     \ | 98 | Test helper functions
     \ | 154 | Test helper functions
     \ | 206 | 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
    
     / | 248 | Test helper functions
     / | 300 | Test helper functions
     | | 355 | Test helper functions
     / | 412 | Test helper functions
     / | 452 | Test helper functions
     / | 480 | Test helper functions
     - | 509 | Test helper functions
     / | 528 | Test helper functions
     | | 559 | Test helper functions
     \ | 570 | Test helper functions
     / | 600 | Test helper functions
     - | 633 | Test helper functions
     \ | 662 | Test helper functions
     - | 669 | Test helper functions
     - | 673 | Test helper functions
     - | 681 | Test helper functions
     \ | 682 | Test helper functions [1] train-rmse:0.943398
    
     \ | 686 | Test helper functions
     / | 696 | Test helper functions
     - | 697 | Test helper functions
     \ | 1 697 | Test helper functions
     | | 1 698 | Test helper functions
     / | 1 699 | Test helper functions
     | | 1 706 | Test helper functions
     | | 1 714 | Test helper functions
     | | 1 734 | Test helper functions
     v | 1 745 | Test helper functions [8.1s]
     --------------------------------------------------------------------------------
     Skip ('test_helpers.R:386:1'): xgb.plot.multi.trees works with and without feature names
     Reason: empty test
     --------------------------------------------------------------------------------
    
     / | 0 | interaction_constraints
     / | 0 | interaction constraints
     - | 1 | interaction constraints
     \ | 2 | interaction constraints
     v | 2 | interaction constraints [9.8s]
    
     / | 0 | interactions
     / | 0 | Test prediction of feature interactions
     - | 1 | Test prediction of feature interactions
     / | 4 | Test prediction of feature interactions
     - | 13 | Test prediction of feature interactions
     | | 15 | 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
     v | 19 | Test prediction of feature interactions [2.2s]
    
     / | 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
    
     - | 1 | Test model IO.
     v | 2 | Test model IO. [0.2s]
    
     / | 0 | model_compatibility
     / | 0 | Models from previous versions of XGBoost can be loaded
     - | 1 | Models from previous versions of XGBoost can be loaded
     / | 8 | Models from previous versions of XGBoost can be loaded
     - | 33 | Models from previous versions of XGBoost can be loaded
     / | 56 | Models from previous versions of XGBoost can be loaded
     | | 79 | Models from previous versions of XGBoost can be loaded
     - | 105 | Models from previous versions of XGBoost can be loaded
     | | 131 | Models from previous versions of XGBoost can be loaded
     - | 157 | Models from previous versions of XGBoost can be loaded
     \ | 182 | Models from previous versions of XGBoost can be loaded
     - | 209 | Models from previous versions of XGBoost can be loaded
     v | 233 | Models from previous versions of XGBoost can be loaded [2.9s]
    
     / | 0 | monotone
     / | 0 | monotone constraints
     - | 1 | monotone constraints
     v | 1 | monotone constraints [0.2s]
    
     / | 0 | parameter_exposure
     / | 0 | Test model params and call are exposed to R
     - | 1 | Test model params and call are exposed to R
     v | 6 | Test model params and call are exposed to R [0.2s]
    
     / | 0 | poisson_regression
     / | 0 | Test Poisson regression model
     v | 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
     [20:33:37] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
     [20:33:37] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
    
     \ | 6 | Learning to rank [20:33:37] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
     [20:33:37] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
     [20:33:37] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
     [20:33:37] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
     [20:33:37] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
     [20:33:37] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
     [20:33:37] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
     [20:33:37] WARNING: src/c_api/c_api.cc:935: `ntree_limit` is deprecated, use `iteration_range` instead.
    
     \ | 14 | Learning to rank
     v | 14 | Learning to rank [0.2s]
    
     / | 0 | update
     / | 0 | update trees in an existing model [20:33:37] 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 [20:33:38] 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.
    
     \ | 2 | update trees in an existing model [20:33:38] 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.
    
     \ | 6 | update trees in an existing model [20:33:38] 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.
    
     | | 7 | update trees in an existing model [20:33:38] 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.
    
     - | 13 | update trees in an existing model [20:33:38] 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 | update trees in an existing model
     v | 19 | update trees in an existing model [1.1s]
    
     == Results =====================================================================
     Duration: 127.3 s
    
     -- Skipped tests --------------------------------------------------------------
     * empty test (1)
    
     [ FAIL 0 | WARN 2 | SKIP 1 | PASS 1316 ]
     >
     > proc.time()
     user system elapsed
     133.91 4.29 131.15
Flavor: r-oldrel-windows-ix86+x86_64