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bonsai  

Model Wrappers for Tree-Based Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("bonsai", "0.4.0")



Attach the package and use:
library("bonsai")
Maintained by
Simon Couch
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-06-23
Latest Update: 2025-06-25
Description:
Bindings for additional tree-based model engines for use with the 'parsnip' package. Models include gradient boosted decision trees with 'LightGBM' (Ke et al, 2017.) and conditional inference trees and conditional random forests with 'partykit' (Hothorn and Zeileis, 2015. and Hothorn et al, 2006. ).
How to cite:
Simon Couch (2022). bonsai: Model Wrappers for Tree-Based Models. R package version 0.4.0, https://cran.r-project.org/web/packages/bonsai. Accessed 15 Jul. 2026.
Previous versions and publish date:
(2026-07-09 07:22), 0.1.0 (2022-06-23 09:20), 0.2.0 (2022-08-31 19:00), 0.2.1 (2022-11-29 20:10), 0.3.0 (2024-06-24 00:30), 0.3.1 (2024-07-23 17:00), 0.3.2 (2025-02-12 00:30), 0.4.0 (2025-06-25 14:30)
Other packages that cited bonsai R package
View bonsai citation profile
Other R packages that bonsai depends, imports, suggests or enhances
Complete documentation for bonsai
Functions, R codes and Examples using the bonsai R package
Some associated functions: bonsai-package . lightgbm_helpers . reexports . train_lightgbm . 
Some associated R codes: 0_imports.R . bonsai_package.R . lightgbm.R . lightgbm_data.R . partykit_data.R . zzz.R .  Full bonsai package functions and examples
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