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treeshap
View on CRAN: Click
here
Download and install treeshap package within the R console
Install from CRAN:
install.packages("treeshap")
Install from Github:
library("remotes")
install_github("cran/treeshap")
Install by package version:
library("remotes")
install_version("treeshap", "0.3.1")
Attach the package and use:
library("treeshap")
Maintained by
Mateusz Krzyzinski
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.treeshap . https://github.com/ModelOriented/treeshap/issues . https://modeloriented.github.io/treeshap/ . https://github.com/ModelOriented/treeshap . treeshap results . treeshap.pdf . treeshap_0.3.1.tar.gz . treeshap_0.3.1.zip . treeshap_0.3.1.zip . treeshap_0.3.1.zip . treeshap_0.3.1.tgz . treeshap_0.3.1.tgz . treeshap_0.3.1.tgz . treeshap_0.3.1.tgz . treeshap_0.3.1.tgz . treeshap_0.3.1.tgz . treeshap archive . https://CRAN.R-project.org/package=treeshap .
First Published: 2023-10-01
Latest Update: 2024-01-22
Description:
An efficient implementation of the 'TreeSHAP' algorithm introduced by Lundberg et al., (2020) <doi:10.1038/s42256-019-0138-9>. It is capable of calculating SHAP (SHapley Additive exPlanations) values for tree-based models in polynomial time.Currently supported models include 'gbm', 'randomForest', 'ranger', 'xgboost', 'lightgbm'.
How to cite:
Mateusz Krzyzinski (2023). treeshap: Compute SHAP Values for Your Tree-Based Models Using the 'TreeSHAP' Algorithm. R package version 0.3.1, https://cran.r-project.org/web/packages/treeshap. Accessed 13 Apr. 2025.
Other packages that cited treeshap R package
View treeshap citation profile
Other R packages that treeshap depends,
imports, suggests or enhances
Complete documentation for treeshap
Functions, R codes and Examples using
the treeshap R package
Some associated functions: colors_drwhy . fifa20 . gbm.unify . is.model_unified . is.treeshap . lightgbm.unify . model_unifiedject . model_unified_multioutputject . plot_contribution . plot_feature_dependence . plot_feature_importance . plot_interaction . predict.model_unified . print.model_unified . print.model_unified_multioutput . print.treeshap . print.treeshap_multioutput . randomForest.unify . ranger.unify . ranger_surv.unify . set_reference_dataset . theme_drwhy . treeshap . treeshapject . treeshap_multioutputject . unify . xgboost.unify .
Some associated R codes: RcppExports.R . fifa20.R . globals.R . model_unified.R . plot_contribution.R . plot_feature_dependence.R . plot_feature_importance.R . plot_interaction.R . predict.R . set_reference_dataset.R . theme_drwhy.R . treeshap.R . unify.R . unify_gbm.R . unify_lightgbm.R . unify_randomForest.R . unify_ranger.R . unify_ranger_surv.R . unify_xgboost.R . Full treeshap package functions and examples
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