Print Diagnostic Model Summary

Prints a formatted summary of the evaluation metrics for a diagnostic model, either from training data or new data evaluation.

Usage

print_model_summary_dia(model_name, results_list, on_new_data = FALSE)

Arguments

model_name

A character string, the name of the model (e.g., "rf", "Bagging (RF)").

results_list

A list containing model evaluation results, typically an element from the output of models_dia() or the result of bagging_dia(), stacking_dia(), voting_dia(), or imbalance_dia(). It must contain evaluation_metrics and model_object (if applicable).

on_new_data

Logical, indicating whether the results are from applying the model to new, unseen data (TRUE) or from the training/internal validation data (FALSE).

Value

NULL. Prints the summary to the console.

Examples

# Example for a successfully evaluated model
successful_results <- list(
  evaluation_metrics = list(
    Threshold_Strategy = "f1",
    `_Threshold` = 0.45,
    AUROC = 0.85, AUROC_95CI_Lower = 0.75, AUROC_95CI_Upper = 0.95,
    AUPRC = 0.80, Accuracy = 0.82, F1 = 0.78,
    Precision = 0.79, Recall = 0.77, Specificity = 0.85
  )
)
print_model_summary_dia("MyAwesomeModel", successful_results)
#> 
#> --- MyAwesomeModel Model (on Training Data) Metrics ---
#> Threshold Strategy: f1 (0.4500)
#> AUROC: 0.8500 (95% CI: 0.7500 - 0.9500)
#> AUPRC: 0.8000
#> Accuracy: 0.8200
#> F1: 0.7800
#> Precision: 0.7900
#> Recall: 0.7700
#> Specificity: 0.8500
#> --------------------------------------------------

# Example for a failed model
failed_results <- list(evaluation_metrics = list(error = "Training failed"))
print_model_summary_dia("MyFailedModel", failed_results)
#> Model: MyFailedModel | Status: Failed (Training failed)