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gbm
View on CRAN: Click
here
Download and install gbm package within the R console
Install from CRAN:
install.packages("gbm")
Install from Github:
library("remotes")
install_github("cran/gbm")
Install by package version:
library("remotes")
install_version("gbm", "2.2.2")
Attach the package and use:
library("gbm")
Maintained by
Greg Ridgeway
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.gbm . https://github.com/gbm-developers/gbm/issues . https://github.com/gbm-developers/gbm . gbm results . gbm.pdf . Generalized Boosted Models: A guide to the gbm package . gbm_2.2.2.tar.gz . gbm_2.2.2.zip . gbm_2.2.2.zip . gbm_2.2.2.zip . gbm_2.2.2.tgz . gbm_2.2.2.tgz . gbm_2.2.2.tgz . gbm_2.2.2.tgz . gbm_2.2.2.tgz . gbm_2.2.2.tgz . gbm archive . gbm2sas . gbm.auto . https://CRAN.R-project.org/package=gbm .
First Published: 2003-02-21
Latest Update: 2024-01-10
Description:
An implementation of extensions to Freund and Schapire's AdaBoost
algorithm and Friedman's gradient boosting machine. Includes regression
methods for least squares, absolute loss, t-distribution loss, quantile
regression, logistic, multinomial logistic, Poisson, Cox proportional hazards
partial likelihood, AdaBoost exponential loss, Huberized hinge loss, and
Learning to Rank measures (LambdaMart). Originally developed by Greg Ridgeway.
Newer version available at github.com/gbm-developers/gbm3.
How to cite:
Greg Ridgeway (2003). gbm: Generalized Boosted Regression Models. R package version 2.2.2, https://cran.r-project.org/web/packages/gbm. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.6 (2003-02-21 18:07), 0.7-1 (2003-03-11 20:04), 0.7-2 (2003-03-14 10:15), 0.7 (2003-03-10 11:37), 1.0 (2003-07-15 20:32), 1.1-1 (2003-12-07 22:39), 1.1-2 (2004-04-10 16:37), 1.2 (2004-06-25 14:09), 1.3-3 (2004-11-04 16:43), 1.3-5 (2004-11-09 09:24), 1.4-2 (2005-03-31 08:54), 1.5-1 (2005-06-02 09:57), 1.5-3 (2005-10-07 22:49), 1.5-5 (2006-01-21 12:58), 1.5-7 (2006-04-18 11:58), 1.5 (2005-05-09 22:56), 1.6-1 (2007-06-14 08:29), 1.6-2 (2007-06-23 10:00), 1.6-3.1 (2010-05-07 18:19), 1.6-3.2 (2012-12-09 19:28), 1.6-3 (2007-08-04 10:05), 2.0-5 (2012-12-08 16:28), 2.0-8 (2013-01-18 10:51), 2.1.1 (2015-03-11 09:02), 2.1.2 (2017-03-21 07:07), 2.1.3 (2017-03-21 07:48), 2.1.4 (2018-09-16 08:20), 2.1.5 (2019-01-14 16:00), 2.1.8.1 (2022-08-11 18:15), 2.1.8 (2020-07-15 12:00), 2.1.9 (2024-01-10 22:23), 2.1 (2013-05-10 20:13)
Other packages that cited gbm R package
View gbm citation profile
Other R packages that gbm depends,
imports, suggests or enhances
Complete documentation for gbm
Functions, R codes and Examples using
the gbm R package
Some associated functions: basehaz.gbm . calibrate.plot . gbm-internals . gbm-package . gbm.fit . gbm.more . gbm . gbmject . gbm.perf . gbm.roc.area . gbmCrossVal . interact.gbm . plot.gbm . predict.gbm . pretty.gbm.tree . print.gbm . quantile.rug . reconstructGBMdata . relative.influence . summary.gbm . test.gbm .
Some associated R codes: basehaz.gbm.R . calibrate.plot.R . gbm-internals.R . gbm-package.R . gbm.R . gbm.fit.R . gbm.more.R . gbmject.R . gbm.perf.R . gbmCrossVal.R . interact.gbm.R . ir.measures.R . plot.gbm.R . predict.gbm.R . pretty.gbm.tree.R . print.gbm.R . reconstructGBMdata.R . relative.influence.R . test.gbm.R . utils.R . zzz.R . Full gbm package functions and examples
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