Using the package ’tuneRanger’ (corresponding to method TRF in our benchmark), the results are extremely similar for all three measures (acc: 0.722, auc: 0.7989, brier: 0.184), indicating that, for this dataset, the default values are adequate. Using the package ’glmnet’ to fit a ridge logistic regression model (with the penalty parameter chosen by internal cross-validation, as done by default in ’glmnet’), the results are also similar: 0.728 for acc, 0.795 for auc and 0.189 for brier.
