ingredients: 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) <arXiv:1806.08915>.

Version: 0.3.1
Depends: R (≥ 3.0)
Imports: DALEX, ggplot2
Suggests: gbm, gower, randomForest, titanic, xgboost, testthat, dplyr, r2d3, ggpubr, jsonlite
Published: 2019-04-09
Author: Przemyslaw Biecek ORCID iD [aut, cre], Hubert Baniecki [ctb]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek at>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
Materials: NEWS
CRAN checks: ingredients results


Reference manual: ingredients.pdf
Package source: ingredients_0.3.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: ingredients_0.3.1.tgz, r-oldrel: ingredients_0.3.1.tgz

Reverse dependencies:

Reverse imports: localModel


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