plot_tuning_results: Plotting Tuner Search Results

In MLwrap: Machine Learning Modelling for Everyone

Plotting Tuner Search Results

Description

The plot_tuning_results() function generates graphical representations of hyperparameter search results, automatically adapting to the type of optimizer used. When Bayesian optimization is employed, the function presents additional plots showing the iterative evolution of the loss function and search results throughout the optimization process. This function validates that model fitting has been completed and that hyperparameter tuning was actually performed before attempting to display results.

Usage

plot_tuning_results(analysis_object)

Arguments

analysis_object

Fitted analysis_object with 'fine_tuning()'.

Value

analysis_object

Examples

# Note: For obtaining the plot with tuning results the user needs to complete till
# fine_tuning( ) function of the MLwrap pipeline.



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 tuning results plot.

plot_tuning_results(wrap_object)

MLwrap documentation built on Aug. 8, 2025, 6:43 p.m.