Model Ingredients

Overview

The ingredients package is a collection of tools for assessment of feature importance and feature effects.

Key functions:

feature_importance() for assessment of global level feature importance,
ceteris_paribus() for calculation of the Ceteris Paribus / What-If Profiles (read more at https://pbiecek.github.io/PM_VEE/ceterisParibus.html),
partial_dependency() for Partial Dependency Plots,
conditional_dependency() for Conditional Dependency Plots also called M Plots,
accumulated_dependency() for Accumulated Local Effects Plots,
aggregate_profiles() and cluster_profiles() for aggregation of Ceteris Paribus Profiles,
aspect_importance() for LIME style explanations,
calculate_oscillations() for calculation of the Ceteris Paribus Oscillations (read more at https://pbiecek.github.io/PM_VEE/ceterisParibusOscillations.html),
ceteris_paribus_2d() for Ceteris Paribus 2D Profiles (read more at https://pbiecek.github.io/PM_VEE/ceterisParibus2d.html),
generic print() and plot() for better usability of selected explainers,
generic plotD3() for interactive, D3 based explanations,
generic describe() for explanations in natural language.

The philosophy behind ingredients explanations is described in the Predictive Models: Explore, Explain, and Debug e-book. The ingredients package is a part of DrWhy.AI universe.

Installation

# the easiest way to get ingredients is to install it from CRAN:
install.packages("ingredients")

# Or the the development version from GitHub:
# install.packages("devtools")
devtools::install_github("ModelOriented/ingredients")