Model Agnostic Instance Level Variable Attributions

Model agnostic tool for decomposition of predictions from black boxes. Supports additive attributions and attributions with interactions. The Break Down Table shows contributions of every variable to a final prediction. The Break Down Plot presents variable contributions in a concise graphical way. This package works for classification and regression models. It is an extension of the 'breakDown' package (Staniak and Biecek 2018) , with new and faster strategies for orderings. It supports interactions in explanations and has interactive visuals (implemented with 'D3.js' library). The methodology behind is described in the 'iBreakDown' article (Gosiewska and Biecek 2019) This package is a part of the 'DrWhy.AI' universe (Biecek 2018) .


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install.packages("iBreakDown")

0.9.5 by Przemyslaw Biecek, 14 days ago


https://ModelOriented.github.io/iBreakDown/


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


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


Authors: Przemyslaw Biecek [aut, cre] , Alicja Gosiewska [aut] , Dariusz Komosinski [ctb]


Documentation:   PDF Manual  


GPL-2 license


Imports ggplot2, DALEX

Suggests knitr, rmarkdown, caret, randomForest, e1071, xgboost, ranger, nnet, testthat, r2d3


See at CRAN