table_evaluation_results {MLwrap} | R Documentation |
Evaluation Results
Description
The table_evaluation_results() function provides access to trained model evaluation metrics, automatically adapting to the type of problem being analyzed. For binary classification problems, it returns a unified table with performance metrics, while for multiclass classification it generates separate tables for training and test data, enabling comparative performance evaluation and detection of potential overfitting.
Usage
table_evaluation_results(analysis_object, show_table = FALSE)
Arguments
analysis_object |
Fitted analysis_object with 'fine_tuning()'. |
show_table |
Boolean. Whether to show the table. |
Value
Tibble or list of tibbles (multiclass classification) with evaluation results.
Examples
# Note: For obtaining the evaluation table the user needs to
# complete till fine_tuning( ) function.
wrap_object <- preprocessing(df = sim_data,
formula = psych_well ~ depression + emot_intel + resilience,
task = "regression")
wrap_object <- build_model(wrap_object, "Random Forest")
wrap_object <- fine_tuning(wrap_object, "Bayesian Optimization")
# And then, you can obtain the evaluation table.
table_results <- table_evaluation_results(wrap_object)
[Package MLwrap version 0.1.0 Index]