plot_tuning_results {MLwrap} | R Documentation |
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)
[Package MLwrap version 0.1.0 Index]