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.
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.
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,
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,
plot()for better usability of selected explanations,
plotD3()for interactive, D3 based explanations,
describe()for explanations in natural language.
# 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
aggregated_profiles() also work with D3:
see an example.
Work on this package was financially supported by the
NCN Opus grant 2016/21/B/ST6/02176.