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ingredients
View on CRAN: Click
here
Download and install ingredients package within the R console
Install from CRAN:
install.packages("ingredients")
Install from Github:
library("remotes")
install_github("cran/ingredients") Install by package version:
library("remotes")
install_version("ingredients", "2.3.0") Attach the package and use:
library("ingredients")
Maintained by
Przemyslaw Biecek
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-04-09
Latest Update: 2023-01-15
Description:
Collection of tools for assessment of feature importance and feature effects.
Key functions are:
feature_importance() for assessment of global level feature importance,
ceteris_paribus() for calculation of the what-if plots,
partial_dependence() for partial dependence plots,
conditional_dependence() for conditional dependence plots,
accumulated_dependence() for accumulated local effects plots,
aggregate_profiles() and cluster_profiles() for aggregation of ceteris paribus profiles,
generic print() and plot() for better usability of selected explainers,
generic plotD3() for interactive, D3 based explanations, and
generic describe() for explanations in natural language.
The package 'ingredients' is a part of the 'DrWhy.AI' universe (Biecek 2018) .
How to cite:
Przemyslaw Biecek (2019). ingredients: Effects and Importances of Model Ingredients. R package version 2.3.0, https://cran.r-project.org/web/packages/ingredients. Accessed 06 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:49), 0.3.1 (2019-04-09 14:10), 0.3.3 (2019-05-01 22:40), 0.3.9 (2019-08-27 00:10), 0.4 (2019-10-27 21:50), 0.5.0 (2019-12-20 07:30), 1.0 (2020-02-18 10:20), 1.1 (2020-03-11 07:30), 1.2.0 (2020-04-20 21:30), 1.3.0 (2020-07-01 23:10), 1.3.1 (2020-07-29 14:00), 2.0.1 (2021-02-05 12:50), 2.0 (2020-09-01 11:50), 2.2.0 (2021-04-10 12:10)
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Complete documentation for ingredients
Functions, R codes and Examples using
the ingredients R package
Some associated functions: accumulated_dependence . aggregate_profiles . bind_plots . calculate_oscillations . calculate_variable_profile . calculate_variable_split . ceteris_paribus . ceteris_paribus_2d . cluster_profiles . conditional_dependence . describe . feature_importance . partial_dependence . plot.aggregated_profiles_explainer . plot.ceteris_paribus_2d_explainer . plot.ceteris_paribus_explainer . plot.ceteris_paribus_oscillations . plot.feature_importance_explainer . plotD3_aggregated_profiles . plotD3_ceteris_paribus . plotD3_feature_importance . print.aggregated_profiles_explainer . print.ceteris_paribus_explainer . print.feature_importance_explainer . select_neighbours . select_sample . show_aggregated_profiles . show_observations . show_profiles . show_residuals . show_rugs .
Some associated R codes: accumulated_dependence.R . aggregate_profiles.R . bind_plots.R . calculate_oscillations.R . calculate_variable_profile.R . ceteris_paribus.R . ceteris_paribus_2d.R . cluster_profiles.R . conditional_dependence.R . describe_aggregated_profiles.R . describe_ceteris_paribus.R . describe_feature_importance.R . feature_importance.R . partial_dependence.R . plotD3_aggregated_profiles.R . plotD3_ceteris_paribus.R . plotD3_feature_importance.R . plot_aggregated_profiles.R . plot_ceteris_paribus.R . plot_ceteris_paribus_2d.R . plot_ceteris_paribus_oscillations.R . plot_feature_importance.R . print_aggregated_profiles.R . print_ceteris_paribus.R . print_feature_importance.R . select_neighbours.R . select_sample.R . show_aggregated_profiles.R . show_observations.R . show_profiles.R . show_residuals.R . show_rugs.R . Full ingredients package functions and examples
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