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 [aut, cre],
Hubert Baniecki [ctb] |
Maintainer: |
Przemyslaw Biecek <przemyslaw.biecek at gmail.com> |
BugReports: |
https://github.com/ModelOriented/ingredients/issues |
License: |
GPL-2 | GPL-3 [expanded from: GPL] |
URL: |
https://ModelOriented.github.io/ingredients/ |
NeedsCompilation: |
no |
Materials: |
NEWS |
CRAN checks: |
ingredients results |
Downloads:
Reverse dependencies:
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