MLwrap (version 0.1.0)

plot_distribution_by_class: Plotting Output Distribution By Class

Description

The plot_distribution_by_class() function generates distributions of model output scores segmented by class, facilitating evaluation of separability between categories and identification of problematic overlaps. This visualization helps assess whether the model produces sufficiently distinct score distributions for different classes.

Usage

plot_distribution_by_class(analysis_object)

Value

analysis_object

Arguments

analysis_object

Fitted analysis_object with 'fine_tuning()'.

Examples

# Note: For obtaining the distribution by class plot the user needs to
# complete till fine_tuning( ) function of the MLwrap pipeline
# and only with categorical outcome.

# \donttest{

wrap_object <- preprocessing(df = sim_data,
                             formula = psych_well_bin ~ depression + emot_intel + resilience,
                             task = "classification")
wrap_object <- build_model(wrap_object, "Random Forest")
wrap_object <- fine_tuning(wrap_object, "Bayesian Optimization")

# And then, you can obtain the distribution by class plot.

plot_distribution_by_class(wrap_object)

# }