modeloriented / ingredients

Effects and Importances of Model Ingredients

Model Ingredients

Overview

The ingredients package is a collection of tools for assessment of feature importance and feature effects. It is imported and used to compute model explanations in multiple packages e.g. DALEX, modelStudio, arenar.

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

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://ema.drwhy.ai/ceterisParibus.html),
• partial_dependence() for Partial Dependence Plots,
• conditional_dependence() for Conditional Dependence Plots also called M Plots,
• accumulated_dependence() for Accumulated Local Effects Plots,
• aggregate_profiles() and cluster_profiles() for aggregation of Ceteris Paribus Profiles,
• calculate_oscillations() for calculation of the Ceteris Paribus Oscillations (read more at https://ema.drwhy.ai/ceterisParibusOscillations.html),
• ceteris_paribus_2d() for Ceteris Paribus 2D Profiles,
• generic print() and plot() for better usability of selected explanations,
• generic plotD3() for interactive, D3 based explanations,
• generic describe() for explanations in natural language.

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")

Interactive plots with D3

feature_importance(), ceteris_paribus() and aggregated_profiles() also work with D3: see an example.

Acknowledgments

Work on this package was financially supported by the NCN Opus grant 2016/21/B/ST6/02176.