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shapr  

Prediction Explanation with Dependence-Aware Shapley Values
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("shapr", "1.1.0")



Attach the package and use:
library("shapr")
Maintained by
Martin Jullum
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-09-03
Latest Update: 2025-04-28
Description:
Complex machine learning models are often hard to interpret. However, in many situations it is crucial to understand and explain why a model made a specific prediction. Shapley values is the only method for such prediction explanation framework with a solid theoretical foundation. Previously known methods for estimating the Shapley values do, however, assume feature independence. This package implements the method described in Aas, Jullum and L
How to cite:
Martin Jullum (2020). shapr: Prediction Explanation with Dependence-Aware Shapley Values. R package version 1.1.0, https://cran.r-project.org/web/packages/shapr. Accessed 30 Oct. 2026.
Previous versions and publish date:
(2026-09-11 23:00), 0.1.2 (2020-09-03 10:20), 0.1.3 (2020-09-04 00:10), 0.1.4 (2021-01-21 17:20), 0.2.0 (2021-01-28 16:30), 0.2.1 (2023-02-27 23:10), 0.2.2 (2023-05-04 16:10), 1.0.1 (2025-01-16 14:00), 1.0.2 (2025-02-07 01:40), 1.0.3 (2025-04-01 12:41), 1.0.4 (2025-04-28 15:00), 1.0.5 (2025-08-25 14:50), 1.0.6 (2025-11-17 16:00), 1.0.7 (2025-12-22 17:30), 1.0.8 (2026-01-20 23:00)
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Complete documentation for shapr
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