MLR3 : Extract predictions in a data table

I have a simple question concerning the extraction of predictions when we do a nested resampling. I don't know how to extract in data table the results from the validation and test sets :

Here is my code :

set.seed(1234)

rr_xgboost = tune_nested(tuner = tnr("mbo"), task = task_imp12, learner = learner_xgboost, inner_resampling = resampling_inner, outer_resampling = resampling_outer, measure = msr("classif.auc"), term_evals = 10, store_models = TRUE, terminator = trm("none"))

xgboost_results_validation <- extract_inner_tuning_results(rr_xgboost)[, .SD, .SDcols = !c("learner_param_vals", "x_domain")]

AUC_validation = xgboost_results_validation$classif.auc

AUC_test = rr_xgboost$score(msr("classif.auc"))

predictions <- rr_xgboost$predictions()
View(predictions)
predictions
[[1]]
<PredictionClassif> for 234 observations:
    row_ids truth response    prob.0    prob.1
          7     0        0 0.5522561 0.4477439
          8     0        0 0.6626639 0.3373361
          9     0        0 0.5247233 0.4752767
---                                           
       1025     0        0 0.8272567 0.1727433
       1026     0        0 0.6095791 0.3904209
       1027     1        0 0.7445868 0.2554132

Thanks to Marc :

Predictions_validation_xgboost <-irr$resample_result[[1]]$predictions()[[1]]
Predictions_test_xgboost <- predictions$prediction[[1]]

Predictions_validation_xgboost <- as.data.table(Predictions_validation_xgboost)
Predictions_test_xgboost <- as.data.table(Predictions_test_xgboost)

Solution

Next time please post a reproducible example.

library(mlr3verse)

tsk_sonar = tsk("sonar")
tnr_grid_search = tnr("grid_search", resolution = 5, batch_size = 5)
lrn_svm = lrn("classif.svm",
  cost  = to_tune(1e-5, 1e5, logscale = TRUE),
  gamma = to_tune(1e-5, 1e5, logscale = TRUE),
  kernel = "radial",
  type = "C-classification"
)
rsmp_cv3 = rsmp("cv", folds = 3)
msr_ce = msr("classif.ce")

at = auto_tuner(
  tuner = tnr_grid_search,
  learner = lrn_svm,
  resampling = rsmp("cv", folds = 4),
  measure = msr_ce,
)

rr = resample(tsk_sonar, at, rsmp_cv3, store_models = TRUE)
rr

irr = extract_inner_tuning_archives(rr) contains all resample results / predictions of the inner loop. You can access the first one with irr$resample_result[[1]]$predictions(). rr$predictions() contains the predictions of the outer loop.