Effects and Importances of Model Ingredients

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_dependency() for partial dependency plots, conditional_dependency() for conditional dependency plots, accumulated_dependency() for accumulated local effects plots, aggregate_profiles() and cluster_profiles() for aggregation of ceteris paribus profiles, theme_drwhy() with a 'ggplot2' skin for all plots, generic print() and plot() for better usability of selected explainers. The package 'ingredients' is a part of the 'DrWhy.AI' universe (Biecek 2018) .


Reference manual

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0.3.1 by Przemyslaw Biecek, 9 days ago


Report a bug at https://github.com/ModelOriented/ingredients/issues

Browse source code at https://github.com/cran/ingredients

Authors: Przemyslaw Biecek [aut, cre] , Hubert Baniecki [ctb]

Documentation:   PDF Manual  

GPL license

Imports DALEX, ggplot2

Suggests gbm, gower, randomForest, titanic, xgboost, testthat, dplyr, r2d3, ggpubr, jsonlite

Imported by localModel.

See at CRAN