Last updated on 2025-12-08 19:50:54 CET.
| Package | ERROR | OK |
|---|---|---|
| mcboost | 13 | |
| mlr3benchmark | 5 | 8 |
| mlr3fda | 13 | |
| mlr3inferr | 13 | |
| mlr3oml | 13 | |
| mlr3torch | 13 |
Current CRAN status: OK: 13
Current CRAN status: ERROR: 5, OK: 8
Version: 0.1.7
Check: examples
Result: ERROR
Running examples in ‘mlr3benchmark-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: autoplot.BenchmarkAggr
> ### Title: Plots for BenchmarkAggr
> ### Aliases: autoplot.BenchmarkAggr
>
> ### ** Examples
>
> if (requireNamespaces(c("mlr3learners", "mlr3", "rpart", "xgboost"))) {
+ library(mlr3)
+ library(mlr3learners)
+ library(ggplot2)
+
+ set.seed(1)
+ task = tsks(c("iris", "sonar", "wine", "zoo"))
+ learns = lrns(c("classif.featureless", "classif.rpart", "classif.xgboost"))
+ learns$classif.xgboost$param_set$values$nrounds = 50
+ bm = benchmark(benchmark_grid(task, learns, rsmp("cv", folds = 3)))
+ obj = as_benchmark_aggr(bm)
+
+ # mean and error bars
+ autoplot(obj, type = "mean", level = 0.95)
+
+ if (requireNamespace("PMCMRplus", quietly = TRUE)) {
+ # critical differences
+ autoplot(obj, type = "cd",style = 1)
+ autoplot(obj, type = "cd",style = 2)
+
+ # post-hoc friedman-nemenyi
+ autoplot(obj, type = "fn")
+ }
+
+ }
INFO [17:08:35.702] [mlr3] Running benchmark with 36 resampling iterations
INFO [17:08:35.722] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3)
INFO [17:08:35.779] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3)
INFO [17:08:35.856] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3)
INFO [17:08:35.928] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3)
INFO [17:08:35.956] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3)
INFO [17:08:35.983] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3)
INFO [17:08:36.010] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 1/3)
INFO [17:08:36.114] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 2/3)
INFO [17:08:36.193] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 3/3)
INFO [17:08:36.271] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3)
INFO [17:08:36.357] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3)
INFO [17:08:36.429] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3)
INFO [17:08:36.512] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
INFO [17:08:36.563] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
INFO [17:08:36.598] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
INFO [17:08:36.631] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 1/3)
INFO [17:08:36.742] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 2/3)
INFO [17:08:36.905] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 3/3)
INFO [17:08:37.049] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 1/3)
INFO [17:08:37.126] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 2/3)
INFO [17:08:37.161] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 3/3)
INFO [17:08:37.190] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 1/3)
INFO [17:08:37.214] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 2/3)
INFO [17:08:37.237] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 3/3)
INFO [17:08:37.262] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 1/3)
INFO [17:08:37.354] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 2/3)
INFO [17:08:37.425] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 3/3)
INFO [17:08:37.536] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 1/3)
INFO [17:08:37.597] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 2/3)
INFO [17:08:37.654] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 3/3)
INFO [17:08:37.714] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 1/3)
INFO [17:08:37.738] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 2/3)
INFO [17:08:37.764] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 3/3)
INFO [17:08:37.788] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 1/3)
INFO [17:08:37.928] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 2/3)
INFO [17:08:38.008] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 3/3)
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
INFO [17:08:38.099] [mlr3] Finished benchmark
Error: Global Friedman test non-significant (p > 0.05), try type = 'mean' instead.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.1.7
Check: examples
Result: ERROR
Running examples in ‘mlr3benchmark-Ex.R’ failed
The error most likely occurred in:
> ### Name: autoplot.BenchmarkAggr
> ### Title: Plots for BenchmarkAggr
> ### Aliases: autoplot.BenchmarkAggr
>
> ### ** Examples
>
> if (requireNamespaces(c("mlr3learners", "mlr3", "rpart", "xgboost"))) {
+ library(mlr3)
+ library(mlr3learners)
+ library(ggplot2)
+
+ set.seed(1)
+ task = tsks(c("iris", "sonar", "wine", "zoo"))
+ learns = lrns(c("classif.featureless", "classif.rpart", "classif.xgboost"))
+ learns$classif.xgboost$param_set$values$nrounds = 50
+ bm = benchmark(benchmark_grid(task, learns, rsmp("cv", folds = 3)))
+ obj = as_benchmark_aggr(bm)
+
+ # mean and error bars
+ autoplot(obj, type = "mean", level = 0.95)
+
+ if (requireNamespace("PMCMRplus", quietly = TRUE)) {
+ # critical differences
+ autoplot(obj, type = "cd",style = 1)
+ autoplot(obj, type = "cd",style = 2)
+
+ # post-hoc friedman-nemenyi
+ autoplot(obj, type = "fn")
+ }
+
+ }
INFO [09:56:14.113] [mlr3] Running benchmark with 36 resampling iterations
INFO [09:56:14.167] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3)
INFO [09:56:14.271] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3)
INFO [09:56:14.379] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3)
INFO [09:56:14.554] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3)
INFO [09:56:14.798] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3)
INFO [09:56:14.990] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3)
INFO [09:56:15.205] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 1/3)
INFO [09:56:15.373] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 2/3)
INFO [09:56:15.563] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 3/3)
INFO [09:56:15.848] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3)
INFO [09:56:16.033] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3)
INFO [09:56:16.087] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3)
INFO [09:56:16.142] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
INFO [09:56:16.251] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
INFO [09:56:16.738] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
INFO [09:56:17.014] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 1/3)
INFO [09:56:17.504] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 2/3)
INFO [09:56:18.322] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 3/3)
INFO [09:56:18.507] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 1/3)
INFO [09:56:18.617] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 2/3)
INFO [09:56:18.699] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 3/3)
INFO [09:56:18.775] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 1/3)
INFO [09:56:18.906] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 2/3)
INFO [09:56:19.058] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 3/3)
INFO [09:56:19.206] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 1/3)
INFO [09:56:19.361] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 2/3)
INFO [09:56:19.745] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 3/3)
INFO [09:56:19.985] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 1/3)
INFO [09:56:20.063] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 2/3)
INFO [09:56:20.198] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 3/3)
INFO [09:56:20.243] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 1/3)
INFO [09:56:20.502] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 2/3)
INFO [09:56:20.584] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 3/3)
INFO [09:56:20.716] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 1/3)
INFO [09:56:20.886] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 2/3)
INFO [09:56:21.060] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 3/3)
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
INFO [09:56:21.350] [mlr3] Finished benchmark
Error: Global Friedman test non-significant (p > 0.05), try type = 'mean' instead.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-clang
Version: 0.1.7
Check: examples
Result: ERROR
Running examples in ‘mlr3benchmark-Ex.R’ failed
The error most likely occurred in:
> ### Name: autoplot.BenchmarkAggr
> ### Title: Plots for BenchmarkAggr
> ### Aliases: autoplot.BenchmarkAggr
>
> ### ** Examples
>
> if (requireNamespaces(c("mlr3learners", "mlr3", "rpart", "xgboost"))) {
+ library(mlr3)
+ library(mlr3learners)
+ library(ggplot2)
+
+ set.seed(1)
+ task = tsks(c("iris", "sonar", "wine", "zoo"))
+ learns = lrns(c("classif.featureless", "classif.rpart", "classif.xgboost"))
+ learns$classif.xgboost$param_set$values$nrounds = 50
+ bm = benchmark(benchmark_grid(task, learns, rsmp("cv", folds = 3)))
+ obj = as_benchmark_aggr(bm)
+
+ # mean and error bars
+ autoplot(obj, type = "mean", level = 0.95)
+
+ if (requireNamespace("PMCMRplus", quietly = TRUE)) {
+ # critical differences
+ autoplot(obj, type = "cd",style = 1)
+ autoplot(obj, type = "cd",style = 2)
+
+ # post-hoc friedman-nemenyi
+ autoplot(obj, type = "fn")
+ }
+
+ }
INFO [10:07:26.930] [mlr3] Running benchmark with 36 resampling iterations
INFO [10:07:26.970] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3)
INFO [10:07:27.042] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3)
INFO [10:07:27.113] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3)
INFO [10:07:27.184] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3)
INFO [10:07:27.243] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3)
INFO [10:07:27.314] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3)
INFO [10:07:27.441] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 1/3)
INFO [10:07:27.674] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 2/3)
INFO [10:07:27.820] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 3/3)
INFO [10:07:27.927] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3)
INFO [10:07:27.999] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3)
INFO [10:07:28.053] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3)
INFO [10:07:28.127] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
INFO [10:07:28.309] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
INFO [10:07:28.547] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
INFO [10:07:28.815] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 1/3)
INFO [10:07:29.332] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 2/3)
INFO [10:07:29.845] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 3/3)
INFO [10:07:30.397] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 1/3)
INFO [10:07:30.588] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 2/3)
INFO [10:07:30.736] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 3/3)
INFO [10:07:30.924] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 1/3)
INFO [10:07:31.060] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 2/3)
INFO [10:07:31.160] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 3/3)
INFO [10:07:31.284] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 1/3)
INFO [10:07:31.609] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 2/3)
INFO [10:07:31.889] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 3/3)
INFO [10:07:32.230] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 1/3)
INFO [10:07:32.406] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 2/3)
INFO [10:07:32.542] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 3/3)
INFO [10:07:32.721] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 1/3)
INFO [10:07:32.900] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 2/3)
INFO [10:07:33.075] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 3/3)
INFO [10:07:33.233] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 1/3)
INFO [10:07:33.634] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 2/3)
INFO [10:07:33.925] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 3/3)
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
INFO [10:07:34.383] [mlr3] Finished benchmark
Error: Global Friedman test non-significant (p > 0.05), try type = 'mean' instead.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc
Version: 0.1.7
Check: examples
Result: ERROR
Running examples in ‘mlr3benchmark-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: autoplot.BenchmarkAggr
> ### Title: Plots for BenchmarkAggr
> ### Aliases: autoplot.BenchmarkAggr
>
> ### ** Examples
>
> if (requireNamespaces(c("mlr3learners", "mlr3", "rpart", "xgboost"))) {
+ library(mlr3)
+ library(mlr3learners)
+ library(ggplot2)
+
+ set.seed(1)
+ task = tsks(c("iris", "sonar", "wine", "zoo"))
+ learns = lrns(c("classif.featureless", "classif.rpart", "classif.xgboost"))
+ learns$classif.xgboost$param_set$values$nrounds = 50
+ bm = benchmark(benchmark_grid(task, learns, rsmp("cv", folds = 3)))
+ obj = as_benchmark_aggr(bm)
+
+ # mean and error bars
+ autoplot(obj, type = "mean", level = 0.95)
+
+ if (requireNamespace("PMCMRplus", quietly = TRUE)) {
+ # critical differences
+ autoplot(obj, type = "cd",style = 1)
+ autoplot(obj, type = "cd",style = 2)
+
+ # post-hoc friedman-nemenyi
+ autoplot(obj, type = "fn")
+ }
+
+ }
INFO [15:53:10.230] [mlr3] Running benchmark with 36 resampling iterations
INFO [15:53:10.263] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3)
INFO [15:53:10.322] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3)
INFO [15:53:10.410] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3)
INFO [15:53:10.486] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3)
INFO [15:53:10.552] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3)
INFO [15:53:10.599] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3)
INFO [15:53:10.636] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 1/3)
INFO [15:53:10.748] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 2/3)
INFO [15:53:10.825] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 3/3)
INFO [15:53:10.898] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3)
INFO [15:53:10.949] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3)
INFO [15:53:11.019] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3)
INFO [15:53:11.054] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
INFO [15:53:11.167] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
INFO [15:53:11.226] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
INFO [15:53:11.282] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 1/3)
INFO [15:53:11.479] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 2/3)
INFO [15:53:11.639] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 3/3)
INFO [15:53:11.770] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 1/3)
INFO [15:53:11.836] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 2/3)
INFO [15:53:11.895] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 3/3)
INFO [15:53:11.956] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 1/3)
INFO [15:53:12.019] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 2/3)
INFO [15:53:12.056] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 3/3)
INFO [15:53:12.127] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 1/3)
INFO [15:53:12.251] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 2/3)
INFO [15:53:12.374] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 3/3)
INFO [15:53:12.486] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 1/3)
INFO [15:53:12.546] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 2/3)
INFO [15:53:12.595] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 3/3)
INFO [15:53:12.657] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 1/3)
INFO [15:53:12.715] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 2/3)
INFO [15:53:12.753] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 3/3)
INFO [15:53:12.819] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 1/3)
INFO [15:53:12.970] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 2/3)
INFO [15:53:13.121] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 3/3)
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
INFO [15:53:13.258] [mlr3] Finished benchmark
Error: Global Friedman test non-significant (p > 0.05), try type = 'mean' instead.
Execution halted
Flavor: r-release-linux-x86_64
Version: 0.1.7
Check: examples
Result: ERROR
Running examples in 'mlr3benchmark-Ex.R' failed
The error most likely occurred in:
> ### Name: autoplot.BenchmarkAggr
> ### Title: Plots for BenchmarkAggr
> ### Aliases: autoplot.BenchmarkAggr
>
> ### ** Examples
>
> if (requireNamespaces(c("mlr3learners", "mlr3", "rpart", "xgboost"))) {
+ library(mlr3)
+ library(mlr3learners)
+ library(ggplot2)
+
+ set.seed(1)
+ task = tsks(c("iris", "sonar", "wine", "zoo"))
+ learns = lrns(c("classif.featureless", "classif.rpart", "classif.xgboost"))
+ learns$classif.xgboost$param_set$values$nrounds = 50
+ bm = benchmark(benchmark_grid(task, learns, rsmp("cv", folds = 3)))
+ obj = as_benchmark_aggr(bm)
+
+ # mean and error bars
+ autoplot(obj, type = "mean", level = 0.95)
+
+ if (requireNamespace("PMCMRplus", quietly = TRUE)) {
+ # critical differences
+ autoplot(obj, type = "cd",style = 1)
+ autoplot(obj, type = "cd",style = 2)
+
+ # post-hoc friedman-nemenyi
+ autoplot(obj, type = "fn")
+ }
+
+ }
INFO [09:04:14.011] [mlr3] Running benchmark with 36 resampling iterations
INFO [09:04:14.040] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 1/3)
INFO [09:04:14.073] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 2/3)
INFO [09:04:14.106] [mlr3] Applying learner 'classif.featureless' on task 'iris' (iter 3/3)
INFO [09:04:14.138] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 1/3)
INFO [09:04:14.193] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 2/3)
INFO [09:04:14.258] [mlr3] Applying learner 'classif.rpart' on task 'iris' (iter 3/3)
INFO [09:04:14.307] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 1/3)
INFO [09:04:14.420] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 2/3)
INFO [09:04:14.528] [mlr3] Applying learner 'classif.xgboost' on task 'iris' (iter 3/3)
INFO [09:04:14.610] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 1/3)
INFO [09:04:14.651] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 2/3)
INFO [09:04:14.700] [mlr3] Applying learner 'classif.featureless' on task 'sonar' (iter 3/3)
INFO [09:04:14.741] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 1/3)
INFO [09:04:14.820] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 2/3)
INFO [09:04:14.898] [mlr3] Applying learner 'classif.rpart' on task 'sonar' (iter 3/3)
INFO [09:04:14.960] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 1/3)
INFO [09:04:15.089] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 2/3)
INFO [09:04:15.181] [mlr3] Applying learner 'classif.xgboost' on task 'sonar' (iter 3/3)
INFO [09:04:15.290] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 1/3)
INFO [09:04:15.332] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 2/3)
INFO [09:04:15.372] [mlr3] Applying learner 'classif.featureless' on task 'wine' (iter 3/3)
INFO [09:04:15.404] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 1/3)
INFO [09:04:15.437] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 2/3)
INFO [09:04:15.484] [mlr3] Applying learner 'classif.rpart' on task 'wine' (iter 3/3)
INFO [09:04:15.536] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 1/3)
INFO [09:04:15.656] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 2/3)
INFO [09:04:15.753] [mlr3] Applying learner 'classif.xgboost' on task 'wine' (iter 3/3)
INFO [09:04:15.825] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 1/3)
INFO [09:04:15.855] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 2/3)
INFO [09:04:15.895] [mlr3] Applying learner 'classif.featureless' on task 'zoo' (iter 3/3)
INFO [09:04:15.927] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 1/3)
INFO [09:04:15.961] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 2/3)
INFO [09:04:15.995] [mlr3] Applying learner 'classif.rpart' on task 'zoo' (iter 3/3)
INFO [09:04:16.029] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 1/3)
INFO [09:04:16.135] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 2/3)
INFO [09:04:16.244] [mlr3] Applying learner 'classif.xgboost' on task 'zoo' (iter 3/3)
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
Warning in check.deprecation(deprecated_train_params, match.call(), ...) :
Passed invalid function arguments: nthread, num_class, eval_metric. These should be passed as a list to argument 'params'. Conversion from argument to 'params' entry will be done automatically, but this behavior will become an error in a future version.
Warning in check.custom.obj(params, objective) :
Argument 'objective' is only for custom objectives. For built-in objectives, pass the objective under 'params'. This warning will become an error in a future version.
INFO [09:04:16.413] [mlr3] Finished benchmark
Error: Global Friedman test non-significant (p > 0.05), try type = 'mean' instead.
Execution halted
Flavor: r-oldrel-windows-x86_64
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.