plot_shap {MLwrap} | R Documentation |
Plotting SHAP Plots
Description
The plot_shap() function implements a comprehensive set of visualizations for SHAP values, including bar plots of mean absolute values, directional plots showing positive or negative contribution nature, box plots illustrating SHAP value distributions by variable, and swarm plots combining individual and distributional information. This multifaceted approach enables deep understanding of how each feature influences model predictions.
Usage
plot_shap(analysis_object, show_table = FALSE)
Arguments
analysis_object |
Fitted analysis_object with 'sensitivity_analysis(methods = "SHAP")'. |
show_table |
Boolean. Whether to print SHAP summarized results table. |
Value
analysis_object
Examples
# Note: For obtaining the SHAP plots the user needs to complete till sensitivity_analysis( )
# function of the MLwrap pipeline using the SHAP method.
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")
wrap_object <- sensitivity_analysis(wrap_object, methods = "SHAP")
# And then, you can obtain the SHAP plots.
plot_shap(wrap_object)
[Package MLwrap version 0.1.0 Index]