Last updated on 2026-01-08 12:49:45 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 2.3.0 | 6.13 | 318.19 | 324.32 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 2.3.0 | 4.73 | 222.54 | 227.27 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 2.3.0 | 11.00 | 527.86 | 538.86 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 2.3.0 | 11.00 | 480.25 | 491.25 | ERROR | |
| r-devel-windows-x86_64 | 2.3.0 | 11.00 | 473.00 | 484.00 | ERROR | |
| r-patched-linux-x86_64 | 2.3.0 | 5.79 | 308.72 | 314.51 | ERROR | |
| r-release-linux-x86_64 | 2.3.0 | 5.79 | 306.98 | 312.77 | ERROR | |
| r-release-macos-arm64 | 2.3.0 | OK | ||||
| r-release-macos-x86_64 | 2.3.0 | 5.00 | 264.00 | 269.00 | OK | |
| r-release-windows-x86_64 | 2.3.0 | 15.00 | 449.00 | 464.00 | ERROR | |
| r-oldrel-macos-arm64 | 2.3.0 | OK | ||||
| r-oldrel-macos-x86_64 | 2.3.0 | 5.00 | 198.00 | 203.00 | OK | |
| r-oldrel-windows-x86_64 | 2.3.0 | 19.00 | 566.00 | 585.00 | ERROR |
Version: 2.3.0
Check: CRAN incoming feasibility
Result: NOTE
Maintainer: ‘Szymon Maksymiuk <sz.maksymiuk@gmail.com>’
The Description field contains
'DALEXtra' creates 'DALEX' Biecek (2018) <arXiv:1806.08915> explainer
Please refer to arXiv e-prints via their arXiv DOI <doi:10.48550/arXiv.YYMM.NNNNN>.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Version: 2.3.0
Check: examples
Result: ERROR
Running examples in ‘DALEXtra-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: explain_xgboost
> ### Title: Create explainer from your xgboost model
> ### Aliases: explain_xgboost
>
> ### ** Examples
>
> library("xgboost")
> library("DALEXtra")
> library("mlr")
Loading required package: ParamHelpers
> # 8th column is target that has to be omitted in X data
> data <- as.matrix(createDummyFeatures(titanic_imputed[,-8]))
> model <- xgboost(data, titanic_imputed$survived, nrounds = 10,
+ params = list(objective = "binary:logistic"),
+ prediction = TRUE)
Warning in throw_err_or_depr_msg("Parameter(s) have been removed from this function: ", :
Parameter(s) have been removed from this function: params. This warning will become an error in a future version.
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized), :
Passed unrecognized parameters: prediction. This warning will become an error in a future version.
> # explainer with encode functiom
> explainer_1 <- explain_xgboost(model, data = titanic_imputed[,-8],
+ titanic_imputed$survived,
+ encode_function = function(data) {
+ as.matrix(createDummyFeatures(data))
+ })
Preparation of a new explainer is initiated
-> model label : xgb.Booster ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.xgb.Booster will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
Error in strsplit(model$params$objective, ":", fixed = TRUE) :
non-character argument
Calls: explain_xgboost ... explain -> model_info -> model_info.xgb.Booster -> strsplit
Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
Version: 2.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [250s/314s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(DALEXtra)
Loading required package: DALEX
Welcome to DALEX (version: 2.5.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
>
> test_check("DALEXtra")
Preparation of a new explainer is initiated
-> model label : LM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : RF
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1785.992 , mean = 3504.747 , max = 6255.43
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -514.8481 , mean = 6.776284 , max = 762.0135
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : GBM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2114.707 , mean = 3501.892 , max = 6056.982
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -519.9033 , mean = 9.631871 , max = 716.1417
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Preparation of a new explainer is initiated
-> model label : ranger ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.ranger will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package ranger , ver. 0.17.0 , task classification ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 0.0135192 , mean = 0.3222933 , max = 0.9920529
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7829657 , mean = -0.0001364879 , max = 0.8893989
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Saving _problems/test_xgboost_explain-13.R
Saving _problems/test_xgboost_explain-31.R
Saving _problems/test_xgboost_explain-50.R
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
══ Skipped tests (11) ══════════════════════════════════════════════════════════
• Conda test env needed for tests (6): 'test_create_env.R:6:3',
'test_create_env.R:27:3', 'test_create_env.R:40:3',
'test_keras_explain.R:6:2', 'test_scikitlearn_explain.R:6:3',
'tests_prints.R:8:3'
• JAVA entry needed for tests (4): 'test_h2o_explain.R:8:3',
'test_h2o_explain.R:33:3', 'test_h2o_explain.R:56:3',
'test_h2o_explain.R:90:3'
• Test with windows (1): 'test_champion_challenger.R:5:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_xgboost_explain.R:11:3'): creating explainer classif ───────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:11:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:29:3'): creating explainer regr ──────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:29:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:48:3'): creating explainer multi ─────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:48:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 2.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [174s/200s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(DALEXtra)
Loading required package: DALEX
Welcome to DALEX (version: 2.5.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
>
> test_check("DALEXtra")
Preparation of a new explainer is initiated
-> model label : LM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : RF
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1786.596 , mean = 3504.628 , max = 6289.819
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -549.8134 , mean = 6.895385 , max = 722.4763
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : GBM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2122.189 , mean = 3504.711 , max = 6037.234
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -560.1272 , mean = 6.812544 , max = 762.9064
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Preparation of a new explainer is initiated
-> model label : ranger ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.ranger will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package ranger , ver. 0.17.0 , task classification ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 0.01490283 , mean = 0.3229277 , max = 0.9911748
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7869268 , mean = -0.0007709748 , max = 0.8936031
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Saving _problems/test_xgboost_explain-13.R
Saving _problems/test_xgboost_explain-31.R
Saving _problems/test_xgboost_explain-50.R
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
══ Skipped tests (11) ══════════════════════════════════════════════════════════
• Conda test env needed for tests (6): 'test_create_env.R:6:3',
'test_create_env.R:27:3', 'test_create_env.R:40:3',
'test_keras_explain.R:6:2', 'test_scikitlearn_explain.R:6:3',
'tests_prints.R:8:3'
• JAVA entry needed for tests (4): 'test_h2o_explain.R:8:3',
'test_h2o_explain.R:33:3', 'test_h2o_explain.R:56:3',
'test_h2o_explain.R:90:3'
• Test with windows (1): 'test_champion_challenger.R:5:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_xgboost_explain.R:11:3'): creating explainer classif ───────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:11:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:29:3'): creating explainer regr ──────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:29:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:48:3'): creating explainer multi ─────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:48:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 2.3.0
Check: examples
Result: ERROR
Running examples in ‘DALEXtra-Ex.R’ failed
The error most likely occurred in:
> ### Name: explain_xgboost
> ### Title: Create explainer from your xgboost model
> ### Aliases: explain_xgboost
>
> ### ** Examples
>
> library("xgboost")
> library("DALEXtra")
> library("mlr")
Loading required package: ParamHelpers
> # 8th column is target that has to be omitted in X data
> data <- as.matrix(createDummyFeatures(titanic_imputed[,-8]))
> model <- xgboost(data, titanic_imputed$survived, nrounds = 10,
+ params = list(objective = "binary:logistic"),
+ prediction = TRUE)
Warning in throw_err_or_depr_msg("Parameter(s) have been removed from this function: ", :
Parameter(s) have been removed from this function: params. This warning will become an error in a future version.
Warning in throw_err_or_depr_msg("Passed unrecognized parameters: ", paste(head(names_unrecognized), :
Passed unrecognized parameters: prediction. This warning will become an error in a future version.
> # explainer with encode functiom
> explainer_1 <- explain_xgboost(model, data = titanic_imputed[,-8],
+ titanic_imputed$survived,
+ encode_function = function(data) {
+ as.matrix(createDummyFeatures(data))
+ })
Preparation of a new explainer is initiated
-> model label : xgb.Booster ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.xgb.Booster will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
Error in strsplit(model$params$objective, ":", fixed = TRUE) :
non-character argument
Calls: explain_xgboost ... explain -> model_info -> model_info.xgb.Booster -> strsplit
Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-release-windows-x86_64, r-oldrel-windows-x86_64
Version: 2.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [7m/17m]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(DALEXtra)
Loading required package: DALEX
Welcome to DALEX (version: 2.5.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
>
> test_check("DALEXtra")
Preparation of a new explainer is initiated
-> model label : LM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : RF
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1799.535 , mean = 3504.868 , max = 6277.874
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -530.406 , mean = 6.655533 , max = 755.8823
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : GBM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2126.907 , mean = 3504.873 , max = 6065.918
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -523.9073 , mean = 6.650176 , max = 717.8616
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Preparation of a new explainer is initiated
-> model label : ranger ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.ranger will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package ranger , ver. 0.17.0 , task classification ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 0.01173537 , mean = 0.3233743 , max = 0.9928707
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7819827 , mean = -0.001217504 , max = 0.8787204
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Saving _problems/test_xgboost_explain-13.R
Saving _problems/test_xgboost_explain-31.R
Saving _problems/test_xgboost_explain-50.R
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
══ Skipped tests (11) ══════════════════════════════════════════════════════════
• Conda test env needed for tests (6): 'test_create_env.R:6:3',
'test_create_env.R:27:3', 'test_create_env.R:40:3',
'test_keras_explain.R:6:2', 'test_scikitlearn_explain.R:6:3',
'tests_prints.R:8:3'
• JAVA entry needed for tests (4): 'test_h2o_explain.R:8:3',
'test_h2o_explain.R:33:3', 'test_h2o_explain.R:56:3',
'test_h2o_explain.R:90:3'
• Test with windows (1): 'test_champion_challenger.R:5:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_xgboost_explain.R:11:3'): creating explainer classif ───────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:11:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:29:3'): creating explainer regr ──────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:29:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:48:3'): creating explainer multi ─────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:48:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 2.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [381s/506s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(DALEXtra)
Loading required package: DALEX
Welcome to DALEX (version: 2.5.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
>
> test_check("DALEXtra")
Preparation of a new explainer is initiated
-> model label : LM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : RF
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1787.108 , mean = 3505.366 , max = 6257.454
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -550.3216 , mean = 6.157272 , max = 756.7292
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : GBM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2117.094 , mean = 3503.09 , max = 6053.704
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -514.0939 , mean = 8.433514 , max = 745.653
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Preparation of a new explainer is initiated
-> model label : ranger ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.ranger will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package ranger , ver. 0.17.0 , task classification ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 0.01209228 , mean = 0.3223495 , max = 0.9899283
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7674164 , mean = -0.0001926773 , max = 0.8822536
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Saving _problems/test_xgboost_explain-13.R
Saving _problems/test_xgboost_explain-31.R
Saving _problems/test_xgboost_explain-50.R
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
══ Skipped tests (11) ══════════════════════════════════════════════════════════
• Conda test env needed for tests (6): 'test_create_env.R:6:3',
'test_create_env.R:27:3', 'test_create_env.R:40:3',
'test_keras_explain.R:6:2', 'test_scikitlearn_explain.R:6:3',
'tests_prints.R:8:3'
• JAVA entry needed for tests (4): 'test_h2o_explain.R:8:3',
'test_h2o_explain.R:33:3', 'test_h2o_explain.R:56:3',
'test_h2o_explain.R:90:3'
• Test with windows (1): 'test_champion_challenger.R:5:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_xgboost_explain.R:11:3'): creating explainer classif ───────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:11:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:29:3'): creating explainer regr ──────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:29:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:48:3'): creating explainer multi ─────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:48:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 2.3.0
Check: tests
Result: ERROR
Running 'testthat.R' [364s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(DALEXtra)
Loading required package: DALEX
Welcome to DALEX (version: 2.5.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
>
> test_check("DALEXtra")
|
| | 0%
|
|============ | 17%
|
|======================= | 33%
|
|=================================== | 50%
|
|=============================================== | 67%
|
|========================================================== | 83%
|
|======================================================================| 100%Preparation of a new explainer is initiated
-> model label : LM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : RF
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1797.949 , mean = 3504.536 , max = 6258.798
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -521.7554 , mean = 6.987466 , max = 759.4371
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : GBM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2127.387 , mean = 3500.043 , max = 6065.034
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -524.3873 , mean = 11.48078 , max = 731.4778
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Preparation of a new explainer is initiated
-> model label : ranger ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.ranger will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package ranger , ver. 0.17.0 , task classification ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 0.01187382 , mean = 0.3218245 , max = 0.9949914
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7900509 , mean = 0.0003322734 , max = 0.8901551
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Saving _problems/test_xgboost_explain-13.R
Saving _problems/test_xgboost_explain-31.R
Saving _problems/test_xgboost_explain-50.R
[ FAIL 3 | WARN 13 | SKIP 10 | PASS 45 ]
══ Skipped tests (10) ══════════════════════════════════════════════════════════
• Conda test env needed for tests (6): 'test_create_env.R:6:3',
'test_create_env.R:27:3', 'test_create_env.R:40:3',
'test_keras_explain.R:6:2', 'test_scikitlearn_explain.R:6:3',
'tests_prints.R:8:3'
• JAVA entry needed for tests (4): 'test_h2o_explain.R:8:3',
'test_h2o_explain.R:33:3', 'test_h2o_explain.R:56:3',
'test_h2o_explain.R:90:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_xgboost_explain.R:11:3'): creating explainer classif ───────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:11:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:29:3'): creating explainer regr ──────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:29:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:48:3'): creating explainer multi ─────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:48:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
[ FAIL 3 | WARN 13 | SKIP 10 | PASS 45 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-windows-x86_64
Version: 2.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [247s/322s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(DALEXtra)
Loading required package: DALEX
Welcome to DALEX (version: 2.5.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
>
> test_check("DALEXtra")
Preparation of a new explainer is initiated
-> model label : LM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : RF
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1790.64 , mean = 3505.511 , max = 6238.673
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -535.2313 , mean = 6.012754 , max = 745.2742
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : GBM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2117.513 , mean = 3505.06 , max = 6060.546
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -544.8215 , mean = 6.463815 , max = 787.2713
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Preparation of a new explainer is initiated
-> model label : ranger ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.ranger will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package ranger , ver. 0.17.0 , task classification ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 0.01005968 , mean = 0.321636 , max = 0.9884774
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7917053 , mean = 0.0005208193 , max = 0.8913589
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Saving _problems/test_xgboost_explain-13.R
Saving _problems/test_xgboost_explain-31.R
Saving _problems/test_xgboost_explain-50.R
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
══ Skipped tests (11) ══════════════════════════════════════════════════════════
• Conda test env needed for tests (6): 'test_create_env.R:6:3',
'test_create_env.R:27:3', 'test_create_env.R:40:3',
'test_keras_explain.R:6:2', 'test_scikitlearn_explain.R:6:3',
'tests_prints.R:8:3'
• JAVA entry needed for tests (4): 'test_h2o_explain.R:8:3',
'test_h2o_explain.R:33:3', 'test_h2o_explain.R:56:3',
'test_h2o_explain.R:90:3'
• Test with windows (1): 'test_champion_challenger.R:5:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_xgboost_explain.R:11:3'): creating explainer classif ───────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:11:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:29:3'): creating explainer regr ──────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:29:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:48:3'): creating explainer multi ─────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:48:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
Error:
! Test failures.
Execution halted
Flavor: r-patched-linux-x86_64
Version: 2.3.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [246s/332s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(DALEXtra)
Loading required package: DALEX
Welcome to DALEX (version: 2.5.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
>
> test_check("DALEXtra")
Preparation of a new explainer is initiated
-> model label : LM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : RF
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1796.827 , mean = 3505.34 , max = 6253.821
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -535.2925 , mean = 6.18343 , max = 748.7196
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : GBM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2137.994 , mean = 3506.508 , max = 6058.709
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -534.9936 , mean = 5.015105 , max = 715.1472
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Preparation of a new explainer is initiated
-> model label : ranger ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.ranger will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package ranger , ver. 0.17.0 , task classification ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 0.01217003 , mean = 0.3222322 , max = 0.9892304
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7945748 , mean = -7.541741e-05 , max = 0.8909769
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Saving _problems/test_xgboost_explain-13.R
Saving _problems/test_xgboost_explain-31.R
Saving _problems/test_xgboost_explain-50.R
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
══ Skipped tests (11) ══════════════════════════════════════════════════════════
• Conda test env needed for tests (6): 'test_create_env.R:6:3',
'test_create_env.R:27:3', 'test_create_env.R:40:3',
'test_keras_explain.R:6:2', 'test_scikitlearn_explain.R:6:3',
'tests_prints.R:8:3'
• JAVA entry needed for tests (4): 'test_h2o_explain.R:8:3',
'test_h2o_explain.R:33:3', 'test_h2o_explain.R:56:3',
'test_h2o_explain.R:90:3'
• Test with windows (1): 'test_champion_challenger.R:5:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_xgboost_explain.R:11:3'): creating explainer classif ───────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:11:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:29:3'): creating explainer regr ──────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:29:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:48:3'): creating explainer multi ─────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:48:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
[ FAIL 3 | WARN 15 | SKIP 11 | PASS 44 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-linux-x86_64
Version: 2.3.0
Check: tests
Result: ERROR
Running 'testthat.R' [343s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(DALEXtra)
Loading required package: DALEX
Welcome to DALEX (version: 2.5.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
>
> test_check("DALEXtra")
|
| | 0%
|
|============ | 17%
|
|======================= | 33%
|
|=================================== | 50%
|
|=============================================== | 67%
|
|========================================================== | 83%
|
|======================================================================| 100%Preparation of a new explainer is initiated
-> model label : LM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : RF
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1800.684 , mean = 3504.064 , max = 6247.21
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -566.3922 , mean = 7.459162 , max = 749.2194
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : GBM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2123.64 , mean = 3502.563 , max = 6045.162
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -520.6401 , mean = 8.960518 , max = 747.5915
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Preparation of a new explainer is initiated
-> model label : ranger ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.ranger will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package ranger , ver. 0.17.0 , task classification ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 0.01325658 , mean = 0.3221525 , max = 0.9931336
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7760095 , mean = 4.288429e-06 , max = 0.8853494
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Saving _problems/test_xgboost_explain-13.R
Saving _problems/test_xgboost_explain-31.R
Saving _problems/test_xgboost_explain-50.R
[ FAIL 3 | WARN 13 | SKIP 10 | PASS 45 ]
══ Skipped tests (10) ══════════════════════════════════════════════════════════
• Conda test env needed for tests (6): 'test_create_env.R:6:3',
'test_create_env.R:27:3', 'test_create_env.R:40:3',
'test_keras_explain.R:6:2', 'test_scikitlearn_explain.R:6:3',
'tests_prints.R:8:3'
• JAVA entry needed for tests (4): 'test_h2o_explain.R:8:3',
'test_h2o_explain.R:33:3', 'test_h2o_explain.R:56:3',
'test_h2o_explain.R:90:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_xgboost_explain.R:11:3'): creating explainer classif ───────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:11:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:29:3'): creating explainer regr ──────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:29:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:48:3'): creating explainer multi ─────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:48:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
[ FAIL 3 | WARN 13 | SKIP 10 | PASS 45 ]
Error:
! Test failures.
Execution halted
Flavor: r-release-windows-x86_64
Version: 2.3.0
Check: tests
Result: ERROR
Running 'testthat.R' [456s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(DALEXtra)
Loading required package: DALEX
Welcome to DALEX (version: 2.5.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
>
> test_check("DALEXtra")
|
| | 0%
|
|============ | 17%
|
|======================= | 33%
|
|=================================== | 50%
|
|=============================================== | 67%
|
|========================================================== | 83%
|
|======================================================================| 100%Preparation of a new explainer is initiated
-> model label : LM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : RF
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1794.756 , mean = 3505.97 , max = 6222.633
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -537.473 , mean = 5.553166 , max = 743.5911
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : GBM
-> data : 9000 rows 6 cols
-> target variable : 9000 values
-> predict function : yhat.WrappedModel will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package mlr , ver. 2.19.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2120.445 , mean = 3507.45 , max = 6053.062
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -564.6235 , mean = 4.073279 , max = 753.4664
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Preparation of a new explainer is initiated
-> model label : ranger ( <1b>[33m default <1b>[39m )
-> data : 2207 rows 7 cols
-> target variable : 2207 values
-> predict function : yhat.ranger will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package ranger , ver. 0.17.0 , task classification ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 0.01192326 , mean = 0.3223503 , max = 0.9908592
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7925012 , mean = -0.0001935299 , max = 0.8815848
<1b>[32m A new explainer has been created! <1b>[39m
additional arguments ignored in warning()
Saving _problems/test_xgboost_explain-13.R
Saving _problems/test_xgboost_explain-31.R
Saving _problems/test_xgboost_explain-50.R
[ FAIL 3 | WARN 13 | SKIP 10 | PASS 45 ]
══ Skipped tests (10) ══════════════════════════════════════════════════════════
• Conda test env needed for tests (6): 'test_create_env.R:6:3',
'test_create_env.R:27:3', 'test_create_env.R:40:3',
'test_keras_explain.R:6:2', 'test_scikitlearn_explain.R:6:3',
'tests_prints.R:8:3'
• JAVA entry needed for tests (4): 'test_h2o_explain.R:8:3',
'test_h2o_explain.R:33:3', 'test_h2o_explain.R:56:3',
'test_h2o_explain.R:90:3'
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_xgboost_explain.R:11:3'): creating explainer classif ───────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:11:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:29:3'): creating explainer regr ──────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:29:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
── Error ('test_xgboost_explain.R:48:3'): creating explainer multi ─────────────
Error in `strsplit(model$params$objective, ":", fixed = TRUE)`: non-character argument
Backtrace:
▆
1. └─DALEXtra::explain_xgboost(...) at test_xgboost_explain.R:48:3
2. └─DALEX::explain(...)
3. ├─DALEX::model_info(model, is_multiclass = task_subtype)
4. └─DALEXtra:::model_info.xgb.Booster(model, is_multiclass = task_subtype)
5. └─base::strsplit(model$params$objective, ":", fixed = TRUE)
[ FAIL 3 | WARN 13 | SKIP 10 | PASS 45 ]
Error:
! Test failures.
Execution halted
Flavor: r-oldrel-windows-x86_64