iBreakDown: 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) <doi:10.32614/RJ-2018-072>, 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) <arXiv:1903.11420> This package is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.

Version: 0.9.9
Depends: R (≥ 3.0)
Imports: ggplot2, DALEX
Suggests: knitr, rmarkdown, randomForest, e1071, xgboost, ranger, nnet, testthat, r2d3, jsonlite, caret
Published: 2019-08-26
Author: Przemyslaw Biecek [aut, cre], Alicja Gosiewska [aut], Hubert Baniecki [aut], Adam Izdebski [aut], Dariusz Komosinski [ctb]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek at gmail.com>
BugReports: https://github.com/ModelOriented/iBreakDown/issues
License: GPL-2
URL: https://ModelOriented.github.io/iBreakDown/, https://github.com/ModelOriented/iBreakDown
NeedsCompilation: no
Citation: iBreakDown citation info
Materials: NEWS
CRAN checks: iBreakDown results

Downloads:

Reference manual: iBreakDown.pdf
Vignettes: iBreakDown plots for classification models
vignette_iBreakDown_description
iBreakDown plots for regression models
iBreakDown plots for Sinking of the RMS Titanic
Package source: iBreakDown_0.9.9.tar.gz
Windows binaries: r-devel: iBreakDown_0.9.9.zip, r-release: iBreakDown_0.9.9.zip, r-oldrel: iBreakDown_0.9.9.zip
OS X binaries: r-release: iBreakDown_0.9.9.tgz, r-oldrel: iBreakDown_0.9.9.tgz
Old sources: iBreakDown archive

Reverse dependencies:

Reverse imports: EIX, modelStudio
Reverse suggests: DALEX

Linking:

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