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gbts
View on CRAN: Click
here
Download and install gbts package within the R console
Install from CRAN:
install.packages("gbts")
Install from Github:
library("remotes")
install_github("cran/gbts")
Install by package version:
library("remotes")
install_version("gbts", "1.2.0")
Attach the package and use:
library("gbts")
Maintained by
Waley W. J. Liang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-10-08
Latest Update: 2017-02-27
Description:
An implementation of hyperparameter optimization for Gradient
Boosted Trees on binary classification and regression problems. The current
version provides two optimization methods: Bayesian optimization and random
search. Instead of giving the single best model, the final output is an
ensemble of Gradient Boosted Trees constructed via the method of ensemble
selection.
How to cite:
Waley W. J. Liang (2016). gbts: Hyperparameter Search for Gradient Boosted Trees. R package version 1.2.0, https://cran.r-project.org/web/packages/gbts. Accessed 30 Apr. 2025.
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Other R packages that gbts depends,
imports, suggests or enhances
Complete documentation for gbts
Functions, R codes and Examples using
the gbts R package
Some associated functions: boston_housing . comperf . gbts . german_credit . predict.gbts .
Some associated R codes: data.R . gbts.R . utility.R . Full gbts package functions and examples
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