Python API

Scikit-learn API

MIDRegressor([params_main, params_inter, ...])	Stand-alone Maximum Interpretation Decomposition regressor.
MIDExplainer(estimator[, target_classes, ...])	Surrogate Maximium Interpretation Decomposition explainer.

Model Interpretation

MIDImportance(estimator, **kwargs)	MID Importance.
MIDBreakdown(estimator[, row])	MID Breakdown.
MIDConditional(estimator, variable, **kwargs)	MID Conditional Expectations.

Plotting

plot_effect(estimator, term[, style, theme, ...])	Visualize the estimated main or interaction effect of a fitted MID model with plotnine.
plot_importance(importance[, style, theme, ...])	Visualize the importance scores of the component functions from a fitted MID model with plotnine.
plot_breakdown(breakdown[, style, theme, ...])	Visualize the decomposition of a single prediction into contributions from each component term with plotnine.
plot_conditional(conditional[, style, ...])	Visualize Individual Conditional Expectation (ICE) plots or Centered ICE (c-ICE) plots with plotnine.

Color Themes

color_theme(theme, **kwargs)	Color themes for graphics.
scale_color_theme(theme[, midpoint])	Scale for 'color' aesthetics of plotnine graphics.
scale_colour_theme(theme[, midpoint])	Alias for scale_color_theme().
scale_fill_theme(theme[, midpoint])	Scale for 'fill' aesthetics of plotnine graphics.