Last updated on 2026-01-13 16:50:50 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 2.3.0 | 5.25 | 318.05 | 323.30 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 2.3.0 | 5.18 | 223.44 | 228.62 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 2.3.0 | 13.00 | 547.70 | 560.70 | ERROR | |
| r-devel-linux-x86_64-fedora-gcc | 2.3.0 | 13.00 | 519.38 | 532.38 | ERROR | |
| r-devel-windows-x86_64 | 2.3.0 | 13.00 | 442.00 | 455.00 | ERROR | |
| r-patched-linux-x86_64 | 2.3.0 | 5.79 | 308.72 | 314.51 | ERROR | |
| r-release-linux-x86_64 | 2.3.0 | 5.53 | 305.96 | 311.49 | 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’ [249s/317s]
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 = 1792.95 , mean = 3503.842 , max = 6269.543
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -544.0141 , mean = 7.681461 , max = 763.3904
<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 = 2120.319 , mean = 3504.302 , max = 6065.702
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -517.3194 , mean = 7.22142 , max = 790.2422
<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 = 0.009940852 , mean = 0.3218734 , max = 0.9889487
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7813986 , mean = 0.0002834222 , max = 0.8843183
<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/210s]
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 = 1799.621 , mean = 3504.274 , max = 6254.901
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -534.1112 , mean = 7.249751 , max = 753.6757
<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 = 2126.068 , mean = 3503.656 , max = 6079.265
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -523.0677 , mean = 7.867783 , max = 755.0636
<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 = 0.01227449 , mean = 0.3224014 , max = 0.9935237
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.786904 , mean = -0.0002446082 , max = 0.8901077
<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/24m]
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 = 1794.384 , mean = 3505.13 , max = 6282.577
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -558.8818 , mean = 6.393675 , max = 763.3037
<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 = 2121.282 , mean = 3504.401 , max = 6058.734
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -518.2821 , mean = 7.122077 , max = 755.2511
<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 = 0.01110071 , mean = 0.3222022 , max = 0.9889742
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.8132052 , mean = -4.540151e-05 , max = 0.8826129
<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’ [7m/20m]
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 = 1795.603 , mean = 3504.55 , max = 6285.622
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -553.8089 , mean = 6.973103 , max = 747.2195
<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 = 2116.807 , mean = 3501.863 , max = 6073.494
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -527.0682 , mean = 9.660097 , max = 763.2702
<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 = 0.01700698 , mean = 0.3221705 , max = 0.9914279
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7697044 , mean = -1.368833e-05 , max = 0.8783672
<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' [349s]
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 = 1794.661 , mean = 3505.324 , max = 6266.996
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -524.9609 , mean = 6.199897 , max = 774.3105
<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 = 2115.279 , mean = 3503.476 , max = 6061.628
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -512.4875 , mean = 8.047946 , max = 655.7839
<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 = 0.01640885 , mean = 0.3219521 , max = 0.9889262
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7830721 , mean = 0.0002046411 , max = 0.8866204
<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’ [245s/302s]
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 = 1798.296 , mean = 3505.052 , max = 6253.977
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -550.8321 , mean = 6.471836 , max = 762.6468
<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 = 2116.594 , mean = 3504.302 , max = 6054.427
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -513.594 , mean = 7.221845 , max = 776.5745
<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 = 0.01364638 , mean = 0.3226038 , max = 0.9893865
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7762869 , mean = -0.000446982 , max = 0.8832276
<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' [466s]
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 = 1798.106 , mean = 3504.724 , max = 6272.415
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -543.6485 , mean = 6.799751 , max = 726.8453
<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 = 2117.785 , mean = 3501.669 , max = 6064.146
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -555.9827 , mean = 9.854346 , max = 684.671
<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 = 0.01432631 , mean = 0.3216604 , max = 0.9895841
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -0.7777019 , mean = 0.0004963902 , max = 0.8785971
<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