MLwrap (version 0.1.0)

plot_lift_curve: Plotting Lift Curve

Description

The plot_lift_curve() function produces lift curves that display the lift factor as a function of population percentile. This visualization is particularly useful for direct marketing applications, showing how much better the model performs compared to random selection at different population segments.

Usage

plot_lift_curve(analysis_object)

Value

analysis_object

Arguments

analysis_object

Fitted analysis_object with 'fine_tuning()'.

Examples

# Note: For obtaining the lift curve 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 lift curve plot.

plot_lift_curve(wrap_object)

# }