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iBreakDown  

Model Agnostic Instance Level Variable Attributions
View on CRAN: Click here


Download and install iBreakDown package within the R console
Install from CRAN:
install.packages("iBreakDown")

Install from Github:
library("remotes")
install_github("cran/iBreakDown")

Install by package version:
library("remotes")
install_version("iBreakDown", "2.1.2")



Attach the package and use:
library("iBreakDown")
Maintained by
Przemyslaw Biecek
[Scholar Profile | Author Map]
First Published: 2019-04-04
Latest Update: 2023-12-01
Description:
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) .
How to cite:
Przemyslaw Biecek (2019). iBreakDown: Model Agnostic Instance Level Variable Attributions. R package version 2.1.2, https://cran.r-project.org/web/packages/iBreakDown. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.9.5 (2019-04-04 14:20), 0.9.6 (2019-04-30 19:10), 0.9.9 (2019-08-27 00:50), 1.0 (2020-02-18 15:10), 1.1.1 (2020-04-15 07:50), 1.2.0 (2020-04-20 21:30), 1.3.1 (2020-07-29 14:00), 2.0.1 (2021-05-07 15:50)
Other packages that cited iBreakDown R package
View iBreakDown citation profile
Other R packages that iBreakDown depends, imports, suggests or enhances
Complete documentation for iBreakDown
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