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gbm3  

Generalized Boosted Regression Models
View on CRAN: Click here


Download and install gbm3 package within the R console
Install from CRAN:
install.packages("gbm3")

Install from Github:
library("remotes")
install_github("cran/gbm3")

Install by package version:
library("remotes")
install_version("gbm3", "3.0.2")



Attach the package and use:
library("gbm3")
Maintained by
Greg Ridgeway
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-01-22
Latest Update:
Description:
Extensions to Freund and Schapire's AdaBoost algorithm, Y. Freund and R. Schapire (1997) and Friedman's gradient boosting machine, J.H. Friedman (2001) . Includes regression methods for least squares, absolute loss, t-distribution loss, quantile regression, logistic, Poisson, Cox proportional hazards partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and Learning to Rank measures (LambdaMART).
How to cite:
Greg Ridgeway (2024). gbm3: Generalized Boosted Regression Models. R package version 3.0.2, https://cran.r-project.org/web/packages/gbm3. Accessed 09 Oct. 2026.
Previous versions and publish date:
(2026-07-13 21:00), 3.0.1 (2026-05-13 22:00), 3.0 (2024-01-22 19:00)
Other packages that cited gbm3 R package
View gbm3 citation profile
Other R packages that gbm3 depends, imports, suggests or enhances
Complete documentation for gbm3
Functions, R codes and Examples using the gbm3 R package
Full gbm3 package functions and examples
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