MLwrap (version 0.1.0)

table_evaluation_results: 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)

Value

Tibble or list of tibbles (multiclass classification) with evaluation results.

Arguments

analysis_object

Fitted analysis_object with 'fine_tuning()'.

show_table

Boolean. Whether to show the table.

Examples

# Note: For obtaining the evaluation table the user needs to
# complete till fine_tuning( ) function.

# \donttest{

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)

# }