Nothing
Code
select_best(rcv_results, metric = "random")
Condition
Error in `select_best()`:
! "random" was not in the metric set. Please choose from: "rmse" and "rsq".
Code
select_best(rcv_results, metric = c("rmse", "rsq"))
Condition
Warning in `select_best()`:
2 metrics were given; "rmse" will be used.
Output
# A tibble: 1 x 5
deg_free degree `wt df` `wt degree` .config
<int> <int> <int> <int> <chr>
1 6 2 2 1 Preprocessor05_Model1
Code
best_default_metric <- select_best(rcv_results)
Condition
Warning in `select_best()`:
No value of `metric` was given; "rmse" will be used.
Code
best_rmse <- select_best(rcv_results, metric = "rmse")
Code
select_best(mtcars, metric = "disp")
Condition
Error in `select_best()`:
! No `select_best()` exists for this type of object.
Code
best_default_metric <- show_best(rcv_results)
Condition
Warning in `show_best()`:
No value of `metric` was given; "rmse" will be used.
Code
best_rmse <- show_best(rcv_results, metric = "rmse")
Code
show_best(mtcars, metric = "disp")
Condition
Error in `show_best()`:
! No `show_best()` exists for this type of object.
Code
select_by_one_std_err(rcv_results, metric = "random", deg_free)
Condition
Error in `select_by_one_std_err()`:
! "random" was not in the metric set. Please choose from: "rmse" and "rsq".
Code
select_by_one_std_err(rcv_results, metric = c("rmse", "rsq"), deg_free)
Condition
Warning in `select_by_one_std_err()`:
2 metrics were given; "rmse" will be used.
Output
# A tibble: 1 x 5
deg_free degree `wt df` `wt degree` .config
<int> <int> <int> <int> <chr>
1 6 2 2 1 Preprocessor05_Model1
Code
select_via_default_metric <- select_by_one_std_err(knn_results, K)
Condition
Warning in `select_by_one_std_err()`:
No value of `metric` was given; "roc_auc" will be used.
Code
select_via_roc <- select_by_one_std_err(knn_results, K, metric = "roc_auc")
Code
select_by_one_std_err(rcv_results, metric = "random")
Condition
Error in `select_by_one_std_err()`:
! "random" was not in the metric set. Please choose from: "rmse" and "rsq".
Code
select_by_one_std_err(mtcars, metric = "disp")
Condition
Error in `select_by_one_std_err()`:
! No `select_by_one_std_err()` exists for this type of object.
Code
select_by_one_std_err(knn_results, metric = "roc_auc", weight_funk)
Condition
Error in `select_by_one_std_err()`:
! Could not sort results by `weight_funk`.
Code
select_by_one_std_err(knn_results, metric = "roc_auc", weight_funk, K)
Condition
Error in `select_by_one_std_err()`:
! Could not sort results by `weight_funk`.
Code
select_by_one_std_err(knn_results, metric = "roc_auc", weight_funk, Kay)
Condition
Error in `select_by_one_std_err()`:
! Could not sort results by `weight_funk` and `Kay`.
Code
select_by_one_std_err(knn_results, metric = "roc_auc", weight_funk, desc(K))
Condition
Error in `select_by_one_std_err()`:
! Could not sort results by `weight_funk` and `desc(K)`.
Code
select_by_pct_loss(rcv_results, metric = "random", deg_free)
Condition
Error in `select_by_pct_loss()`:
! "random" was not in the metric set. Please choose from: "rmse" and "rsq".
Code
select_by_pct_loss(rcv_results, metric = c("rmse", "rsq"), deg_free)
Condition
Warning in `select_by_pct_loss()`:
2 metrics were given; "rmse" will be used.
Output
# A tibble: 1 x 5
deg_free degree `wt df` `wt degree` .config
<int> <int> <int> <int> <chr>
1 6 2 2 1 Preprocessor05_Model1
Code
select_via_default_metric <- select_by_pct_loss(knn_results, K)
Condition
Warning in `select_by_pct_loss()`:
No value of `metric` was given; "roc_auc" will be used.
Code
select_via_roc <- select_by_pct_loss(knn_results, K, metric = "roc_auc")
Code
select_by_pct_loss(rcv_results, metric = "random")
Condition
Error in `select_by_pct_loss()`:
! "random" was not in the metric set. Please choose from: "rmse" and "rsq".
Code
select_by_pct_loss(mtcars, metric = "disp")
Condition
Error in `select_by_pct_loss()`:
! No `select_by_pct_loss()` exists for this type of object.
Code
select_by_pct_loss(knn_results, metric = "roc_auc", weight_funk)
Condition
Error in `select_by_pct_loss()`:
! Could not sort results by `weight_funk`.
Code
select_by_pct_loss(knn_results, metric = "roc_auc", weight_funk, K)
Condition
Error in `select_by_pct_loss()`:
! Could not sort results by `weight_funk`.
Code
select_by_pct_loss(knn_results, metric = "roc_auc", weight_funk, Kay)
Condition
Error in `select_by_pct_loss()`:
! Could not sort results by `weight_funk` and `Kay`.
Code
select_by_pct_loss(knn_results, metric = "roc_auc", weight_funk, desc(K))
Condition
Error in `select_by_pct_loss()`:
! Could not sort results by `weight_funk` and `desc(K)`.
Code
show_best(surv_res)
Condition
Warning in `show_best()`:
No value of `metric` was given; "brier_survival" will be used.
Warning in `show_best()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 5 x 8
trees .metric .estimator .eval_time mean n std_err .config
<dbl> <chr> <chr> <dbl> <dbl> <int> <dbl> <chr>
1 100 brier_survival standard 10 0.118 10 0.0177 Preprocessor1_~
2 20 brier_survival standard 10 0.136 10 0.0153 Preprocessor1_~
3 10 brier_survival standard 10 0.155 10 0.0175 Preprocessor1_~
4 5 brier_survival standard 10 0.172 10 0.0198 Preprocessor1_~
5 1 brier_survival standard 10 0.194 10 0.0221 Preprocessor1_~
Code
show_best(surv_res, metric = "concordance_survival")
Output
# A tibble: 5 x 8
trees .metric .estimator .eval_time mean n std_err .config
<dbl> <chr> <chr> <dbl> <dbl> <int> <dbl> <chr>
1 20 concordance_survival standard NA 0.677 10 0.0354 Preproce~
2 100 concordance_survival standard NA 0.670 10 0.0329 Preproce~
3 10 concordance_survival standard NA 0.668 10 0.0376 Preproce~
4 5 concordance_survival standard NA 0.663 10 0.0363 Preproce~
5 1 concordance_survival standard NA 0.626 10 0.0326 Preproce~
Code
show_best(surv_res, metric = "brier_survival_integrated")
Output
# A tibble: 5 x 8
trees .metric .estimator .eval_time mean n std_err .config
<dbl> <chr> <chr> <dbl> <dbl> <int> <dbl> <chr>
1 100 brier_survival_integr~ standard NA 0.117 10 0.00699 Prepro~
2 20 brier_survival_integr~ standard NA 0.127 10 0.00981 Prepro~
3 10 brier_survival_integr~ standard NA 0.141 10 0.0134 Prepro~
4 5 brier_survival_integr~ standard NA 0.151 10 0.0159 Prepro~
5 1 brier_survival_integr~ standard NA 0.164 10 0.0182 Prepro~
Code
show_best(surv_res, metric = "brier_survival")
Condition
Warning in `show_best()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 5 x 8
trees .metric .estimator .eval_time mean n std_err .config
<dbl> <chr> <chr> <dbl> <dbl> <int> <dbl> <chr>
1 100 brier_survival standard 10 0.118 10 0.0177 Preprocessor1_~
2 20 brier_survival standard 10 0.136 10 0.0153 Preprocessor1_~
3 10 brier_survival standard 10 0.155 10 0.0175 Preprocessor1_~
4 5 brier_survival standard 10 0.172 10 0.0198 Preprocessor1_~
5 1 brier_survival standard 10 0.194 10 0.0221 Preprocessor1_~
Code
show_best(surv_res, metric = c("brier_survival", "roc_auc_survival"))
Condition
Warning in `show_best()`:
2 metrics were given; "brier_survival" will be used.
Warning in `show_best()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 5 x 8
trees .metric .estimator .eval_time mean n std_err .config
<dbl> <chr> <chr> <dbl> <dbl> <int> <dbl> <chr>
1 100 brier_survival standard 10 0.118 10 0.0177 Preprocessor1_~
2 20 brier_survival standard 10 0.136 10 0.0153 Preprocessor1_~
3 10 brier_survival standard 10 0.155 10 0.0175 Preprocessor1_~
4 5 brier_survival standard 10 0.172 10 0.0198 Preprocessor1_~
5 1 brier_survival standard 10 0.194 10 0.0221 Preprocessor1_~
Code
show_best(surv_res, metric = "brier_survival", eval_time = 1)
Output
# A tibble: 5 x 8
trees .metric .estimator .eval_time mean n std_err .config
<dbl> <chr> <chr> <dbl> <dbl> <int> <dbl> <chr>
1 20 brier_survival standard 1 0.0381 10 0.0149 Preprocessor1~
2 10 brier_survival standard 1 0.0386 10 0.0151 Preprocessor1~
3 100 brier_survival standard 1 0.0386 10 0.0147 Preprocessor1~
4 5 brier_survival standard 1 0.0389 10 0.0152 Preprocessor1~
5 1 brier_survival standard 1 0.0392 10 0.0153 Preprocessor1~
Code
show_best(surv_res, metric = "concordance_survival", eval_time = 1)
Condition
Warning in `show_best()`:
`eval_time` is only used for dynamic survival metrics.
Output
# A tibble: 5 x 8
trees .metric .estimator .eval_time mean n std_err .config
<dbl> <chr> <chr> <dbl> <dbl> <int> <dbl> <chr>
1 20 concordance_survival standard NA 0.677 10 0.0354 Preproce~
2 100 concordance_survival standard NA 0.670 10 0.0329 Preproce~
3 10 concordance_survival standard NA 0.668 10 0.0376 Preproce~
4 5 concordance_survival standard NA 0.663 10 0.0363 Preproce~
5 1 concordance_survival standard NA 0.626 10 0.0326 Preproce~
Code
show_best(surv_res, metric = "concordance_survival", eval_time = 1.1)
Condition
Warning in `show_best()`:
`eval_time` is only used for dynamic survival metrics.
Output
# A tibble: 5 x 8
trees .metric .estimator .eval_time mean n std_err .config
<dbl> <chr> <chr> <dbl> <dbl> <int> <dbl> <chr>
1 20 concordance_survival standard NA 0.677 10 0.0354 Preproce~
2 100 concordance_survival standard NA 0.670 10 0.0329 Preproce~
3 10 concordance_survival standard NA 0.668 10 0.0376 Preproce~
4 5 concordance_survival standard NA 0.663 10 0.0363 Preproce~
5 1 concordance_survival standard NA 0.626 10 0.0326 Preproce~
Code
show_best(surv_res, metric = "brier_survival", eval_time = 1.1)
Condition
Error in `show_best()`:
! Evaluation time 1.1 is not in the results.
Code
show_best(surv_res, metric = "brier_survival", eval_time = 1:2)
Condition
Warning in `show_best()`:
2 evaluation times are available; the first will be used (i.e. `eval_time = 1`).
Output
# A tibble: 5 x 8
trees .metric .estimator .eval_time mean n std_err .config
<dbl> <chr> <chr> <dbl> <dbl> <int> <dbl> <chr>
1 20 brier_survival standard 1 0.0381 10 0.0149 Preprocessor1~
2 10 brier_survival standard 1 0.0386 10 0.0151 Preprocessor1~
3 100 brier_survival standard 1 0.0386 10 0.0147 Preprocessor1~
4 5 brier_survival standard 1 0.0389 10 0.0152 Preprocessor1~
5 1 brier_survival standard 1 0.0392 10 0.0153 Preprocessor1~
Code
show_best(surv_res, metric = "brier_survival", eval_time = 3:4)
Condition
Warning in `show_best()`:
2 evaluation times are available; the first will be used (i.e. `eval_time = 3`).
Error in `show_best()`:
! Evaluation time 3 is not in the results.
Code
select_best(surv_res)
Condition
Warning in `select_best()`:
No value of `metric` was given; "brier_survival" will be used.
Warning in `select_best()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 100 Preprocessor1_Model5
Code
select_best(surv_res, metric = "concordance_survival")
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 20 Preprocessor1_Model4
Code
select_best(surv_res, metric = "brier_survival_integrated")
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 100 Preprocessor1_Model5
Code
select_best(surv_res, metric = "brier_survival")
Condition
Warning in `select_best()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 100 Preprocessor1_Model5
Code
select_best(surv_res, metric = c("brier_survival", "roc_auc_survival"))
Condition
Warning in `select_best()`:
2 metrics were given; "brier_survival" will be used.
Warning in `select_best()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 100 Preprocessor1_Model5
Code
select_best(surv_res, metric = "brier_survival", eval_time = 1)
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 20 Preprocessor1_Model4
Code
select_best(surv_res, metric = "concordance_survival", eval_time = 1)
Condition
Warning in `select_best()`:
`eval_time` is only used for dynamic survival metrics.
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 20 Preprocessor1_Model4
Code
select_best(surv_res, metric = "concordance_survival", eval_time = 1.1)
Condition
Warning in `select_best()`:
`eval_time` is only used for dynamic survival metrics.
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 20 Preprocessor1_Model4
Code
select_best(surv_res, metric = "brier_survival", eval_time = 1.1)
Condition
Error in `select_best()`:
! Evaluation time 1.1 is not in the results.
Code
select_best(surv_res, metric = "brier_survival", eval_time = 1:2)
Condition
Warning in `select_best()`:
2 evaluation times are available; the first will be used (i.e. `eval_time = 1`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 20 Preprocessor1_Model4
Code
select_best(surv_res, metric = "brier_survival", eval_time = 3:4)
Condition
Warning in `select_best()`:
2 evaluation times are available; the first will be used (i.e. `eval_time = 3`).
Error in `select_best()`:
! Evaluation time 3 is not in the results.
Code
select_by_one_std_err(surv_res, trees)
Condition
Warning in `select_by_one_std_err()`:
No value of `metric` was given; "brier_survival" will be used.
Warning in `select_by_one_std_err()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 20 Preprocessor1_Model4
Code
select_by_one_std_err(surv_res, metric = "concordance_survival", trees)
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 5 Preprocessor1_Model2
Code
select_by_one_std_err(surv_res, metric = "brier_survival_integrated", trees)
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 100 Preprocessor1_Model5
Code
select_by_one_std_err(surv_res, metric = "brier_survival", trees)
Condition
Warning in `select_by_one_std_err()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 20 Preprocessor1_Model4
Code
select_by_one_std_err(surv_res, metric = c("brier_survival", "roc_auc_survival"),
trees)
Condition
Warning in `select_by_one_std_err()`:
2 metrics were given; "brier_survival" will be used.
Warning in `select_by_one_std_err()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 20 Preprocessor1_Model4
Code
select_by_one_std_err(surv_res, metric = "brier_survival", eval_time = 1, trees)
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 1 Preprocessor1_Model1
Code
select_by_one_std_err(surv_res, metric = "concordance_survival", eval_time = 1,
trees)
Condition
Warning in `select_by_one_std_err()`:
`eval_time` is only used for dynamic survival metrics.
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 5 Preprocessor1_Model2
Code
select_by_one_std_err(surv_res, metric = "concordance_survival", eval_time = 1.1,
trees)
Condition
Warning in `select_by_one_std_err()`:
`eval_time` is only used for dynamic survival metrics.
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 5 Preprocessor1_Model2
Code
select_by_one_std_err(surv_res, metric = "brier_survival", eval_time = 1.1,
trees)
Condition
Error in `select_by_one_std_err()`:
! Evaluation time 1.1 is not in the results.
Code
select_by_one_std_err(surv_res, metric = "brier_survival", eval_time = 1:2,
trees)
Condition
Warning in `select_by_one_std_err()`:
2 evaluation times are available; the first will be used (i.e. `eval_time = 1`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 1 Preprocessor1_Model1
Code
select_by_one_std_err(surv_res, metric = "brier_survival", eval_time = 3:4,
trees)
Condition
Warning in `select_by_one_std_err()`:
2 evaluation times are available; the first will be used (i.e. `eval_time = 3`).
Error in `select_by_one_std_err()`:
! Evaluation time 3 is not in the results.
Code
select_by_pct_loss(surv_res, trees)
Condition
Warning in `select_by_pct_loss()`:
No value of `metric` was given; "brier_survival" will be used.
Warning in `select_by_pct_loss()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 100 Preprocessor1_Model5
Code
select_by_pct_loss(surv_res, metric = "concordance_survival", trees)
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 10 Preprocessor1_Model3
Code
select_by_pct_loss(surv_res, metric = "brier_survival_integrated", trees)
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 100 Preprocessor1_Model5
Code
select_by_pct_loss(surv_res, metric = "brier_survival", trees)
Condition
Warning in `select_by_pct_loss()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 100 Preprocessor1_Model5
Code
select_by_pct_loss(surv_res, metric = c("brier_survival", "roc_auc_survival"),
trees)
Condition
Warning in `select_by_pct_loss()`:
2 metrics were given; "brier_survival" will be used.
Warning in `select_by_pct_loss()`:
4 evaluation times are available; the first will be used (i.e. `eval_time = 10`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 100 Preprocessor1_Model5
Code
select_by_pct_loss(surv_res, metric = "brier_survival", eval_time = 1, trees)
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 5 Preprocessor1_Model2
Code
select_by_pct_loss(surv_res, metric = "concordance_survival", eval_time = 1,
trees)
Condition
Warning in `select_by_pct_loss()`:
`eval_time` is only used for dynamic survival metrics.
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 10 Preprocessor1_Model3
Code
select_by_pct_loss(surv_res, metric = "concordance_survival", eval_time = 1.1,
trees)
Condition
Warning in `select_by_pct_loss()`:
`eval_time` is only used for dynamic survival metrics.
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 10 Preprocessor1_Model3
Code
select_by_pct_loss(surv_res, metric = "brier_survival", eval_time = 1.1, trees)
Condition
Error in `select_by_pct_loss()`:
! Evaluation time 1.1 is not in the results.
Code
select_by_pct_loss(surv_res, metric = "brier_survival", eval_time = 1:2, trees)
Condition
Warning in `select_by_pct_loss()`:
2 evaluation times are available; the first will be used (i.e. `eval_time = 1`).
Output
# A tibble: 1 x 2
trees .config
<dbl> <chr>
1 5 Preprocessor1_Model2
Code
select_by_pct_loss(surv_res, metric = "brier_survival", eval_time = 3:4, trees)
Condition
Warning in `select_by_pct_loss()`:
2 evaluation times are available; the first will be used (i.e. `eval_time = 3`).
Error in `select_by_pct_loss()`:
! Evaluation time 3 is not in the results.
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