xgboost

R 패키지 메타데이터와 수집 신호를 모아 봅니다.

Packages / CRAN / xgboost

xgboost

v3.2.1.1
Repository CRANLicense Apache License (== 2.0) | file LICENSELifecycle activeNeeds compilation yes
DOI
10.32614/CRAN.package.xgboost
Task views
Databases with R, High-Performance and Parallel Computing with R, Machine Learning & Statistical Learning, Model Deployment with R, Survival Analysis
Reverse imports
3,459
Reverse depends
119

Core Signals

첫 화면에서 판단해야 할 수집 신호를 먼저 배치합니다.

3
Task views
Databases with R, High-Performance and Parallel Computing with R, Machine Learning & Statistical Learning 외 2
Reverse imports
3,459
Reverse depends
119

Supported Backends

DESCRIPTION에서 감지한 backend 관련 package입니다.

1
D
data.table
Imports

Quick Facts

기본 메타데이터를 작은 카드와 토큰으로 압축합니다.

profile
Repository
CRAN
Version
3.2.1.1
License
Apache License (== 2.0) | file LICENSE
Lifecycle
active
Needs compilation
yes
Reverse depends
119
Reverse imports
3,459
Last observed
2026-05-30
CRAN
cran.r-project.org/package=xgboost

수집 소스별 패키지 정보

1개 소스
CRAN
3.2.1.1
2026-05-30
License
Apache License (== 2.0) | file LICENSE
Depends
R (>= 4.3.0)
Imports
Matrix (>= 1.1-0), methods, data.table (>= 1.9.6), jsonlite (>= 1.0)
Suggests
knitr, rmarkdown, ggplot2 (>= 1.0.1), DiagrammeR (>= 0.9.0), DiagrammeRsvg, rsvg, htmlwidgets, Ckmeans.1d.dp (>= 3.3.1), vcd (>= 1.3), testthat, igraph (>= 1.0.1), float, titanic, RhpcBLASctl, survival
Needs compilation
yes
Reverse depends
119
Reverse imports
3,459
Lifecycle
active
Last observed
2026-05-30 10:45:11

이 패키지가 의존하는 패키지

5개 표시전체 19개
PackageTypeSpec
data.table
CRAN · 3.2.1.1 · 2026-05-30
Importsdata.table (>= 1.9.6)
jsonlite
CRAN · 3.2.1.1 · 2026-05-30
Importsjsonlite (>= 1.0)
Matrix
CRAN · 3.2.1.1 · 2026-05-30
ImportsMatrix (>= 1.1-0)
methods
CRAN · 3.2.1.1 · 2026-05-30
Importsmethods
Ckmeans.1d.dp
CRAN · 3.2.1.1 · 2026-05-30
SuggestsCkmeans.1d.dp (>= 3.3.1)
1 / 4

이 패키지를 쓰는 패키지

5개 표시전체 120개
PackageTypeSpec
LogisticEnsembles
1.0.2
CRAN · 2026-05-30
Dependsxgboost
NumericEnsembles
1.2
CRAN · 2026-05-30
Dependsxgboost
PIE
1.0.0
CRAN · 2026-05-30
Dependsxgboost
adapt4pv
0.2-3
CRAN · 2026-05-30
Importsxgboost
alookr
0.5.1
CRAN · 2026-05-30
Importsxgboost (>= 3.1.2.1)
1 / 24

Reverse dependency summary

4 types
TypePackages
Depends3
Imports89
Suggests88
Enhances2

패키지 페이지

Reverse depends
6
Reverse imports
190
Reverse suggests
186
Reverse enhances
4
All links
242
Repository
CRAN
Version
3.2.1.1
Collected
2026-05-20 17:13:25
Package page
https://cran.r-project.org/web/packages/xgboost/index.html
DOI
10.32614/CRAN.package.xgboost
CRAN checks
https://cran.r-project.org/web/checks/check_results_xgboost.html
Reference HTML
https://cran.r-project.org/web/packages/xgboost/refman/xgboost.html
Reference PDF
https://cran.r-project.org/web/packages/xgboost/xgboost.pdf
Source package
https://cran.r-project.org/src/contrib/xgboost_3.2.1.1.tar.gz
Archive
https://CRAN.R-project.org/src/contrib/Archive/xgboost
In views
DatabasesHighPerformanceComputingMachineLearningModelDeploymentSurvival
Page fields
Author
Tianqi Chen [aut], Tong He [aut], Michael Benesty [aut], Vadim Khotilovich [aut], Yuan Tang [aut], Hyunsu Cho [aut], Kailong Chen [aut], Rory Mitchell [aut], Ignacio Cano [aut], Tianyi Zhou [aut], Mu Li [aut], Junyuan Xie [aut], Min Lin [aut], Yifeng Geng [aut], Yutian Li [aut], Jiaming Yuan [aut, cre], David Cortes [aut], XGBoost contributors [cph] (base XGBoost implementation)
BugReports
https://github.com/dmlc/xgboost/issues
CRAN Checks
xgboost results
DOI
10.32614/CRAN.package.xgboost
In Views
Databases , HighPerformanceComputing , MachineLearning , ModelDeployment , Survival
License
Apache License (== 2.0) | file LICENSE
Maintainer
Jiaming Yuan <jm.yuan at outlook.com>
NeedsCompilation
yes
Old Sources
xgboost archive
Package Source
xgboost_3.2.1.1.tar.gz
Published
2026-03-18
Reference Manual
xgboost.html , xgboost.pdf
Reverse Depends
LogisticEnsembles , NumericEnsembles , PIE
Reverse Enhances
fastshap , vip
Reverse Imports
adapt4pv , alookr , audrex , autoBagging , autostats , bambu , BayesSpace , BioMoR , BioPred , CausalGPS , CCI , cpfa , CRE , csmpv , CytoProfile , ddml , DSAM , DSWE , E2E , EFAfactors , EHRmuse , EIX , fastml , FastRet , fastrmodels , FoRecoML , funcml , ggscidca , glmnetr , GNET2 , HCPclust , IBLM , iimi , imanr , infinityFlow , irboost , IVDML , latentFactoR , ldmppr , LTFGRS , LTFHPlus , MAPFX , MBMethPred , MethScope , MFF , mikropml , mixgb , mlspatial , modeltime , nadir , nfl4th , nflfastR , nsga3 , personalized , PND.heter.cluster , postcard , PoweREST , predhy , predhy.GUI , predictoR , promor , qshap , quickSentiment , radiant.model , reddPrec , ReSurv , RFGeneRank , rminer , roseRF , scDblFinder , scds , scPOEM , SELF , SEMdeep , sentiment.ai , SHAPBoost , SHAPforxgboost , shapviz , simPop , SMMAL , survalis , surveyvoi , tidybins , tidysdm , traineR , TSCI , tsensembler , twang , utsf , VIM , wactor , weightedGCM , xgb2sql , xpect , xrf
Reverse Suggests
automatedRecLin , BAGofT , bigsnpr , bioLeak , biomod2 , BORG , breakDown , bundle , butcher , caretSDM , cfbfastR , CimpleG , ClassifyR , coefplot , comets , cornet , CrcBiomeScreen , cuda.ml , CytoMethIC , DALEXtra , daltoolbox , DeepLearningCausal , drape , e2tree , easyalluvial , embed , explore , familiar , fdm2id , FLAME , flevr , GenericML , h3sdm , interflex , lime , LLMAgentR , MachineShop , MantaID , marginaleffects , mcboost , miesmuschel , misl , mistyR , ml , mlflow , mllrnrs , mlr , mlr3benchmark , mlr3hyperband , mlr3learners , mlr3shiny , mlr3tuning , mlr3tuningspaces , mlr3viz , mlsurvlrnrs , MLwrap , modelStudio , modeltime.ensemble , MSclassifR , offsetreg , OpEnCAST , orbital , parsnip , pathMED , PatientLevelPrediction , pdp , PheCAP , pmml , polle , PortfolioTesteR , qeML , r2pmml , rattle , rBayesianOptimization , rush , sense , shapr , sits , stackgbm , SuperLearner , SuperSurv , survex , tabnet , targeted , tidylearn , tidypopgen , tidypredict , treeshap , tune , vetiver , vimp , vivid , XAItest
SystemRequirements
GNU make, C++17
URL
https://github.com/dmlc/xgboost
Version
3.2.1.1
Vignettes
XGBoost for R introduction ( source , R code ) XGBoost from JSON ( source , R code )
Windows Binaries
r-devel: xgboost_3.2.1.1.zip , r-release: xgboost_3.2.1.1.zip , r-oldrel: xgboost_3.2.1.1.zip
MacOS Binaries
r-release (arm64): xgboost_3.2.1.1.tgz , r-oldrel (arm64): xgboost_3.2.1.1.tgz , r-release (x86_64): xgboost_3.2.1.1.tgz , r-oldrel (x86_64): xgboost_3.2.1.1.tgz
Version
3.2.1.1
Published
2026-03-18
DOI
10.32614/CRAN.package.xgboost
Author
Tianqi Chen [aut], Tong He [aut], Michael Benesty [aut], Vadim Khotilovich [aut], Yuan Tang [aut], Hyunsu Cho [aut], Kailong Chen [aut], Rory Mitchell [aut], Ignacio Cano [aut], Tianyi Zhou [aut], Mu Li [aut], Junyuan Xie [aut], Min Lin [aut], Yifeng Geng [aut], Yutian Li [aut], Jiaming Yuan [aut, cre], David Cortes [aut], XGBoost contributors [cph] (base XGBoost implementation)
Maintainer
Jiaming Yuan <jm.yuan at outlook.com>
BugReports
https://github.com/dmlc/xgboost/issues
License
Apache License (== 2.0) | file LICENSE
URL
https://github.com/dmlc/xgboost
NeedsCompilation
yes
SystemRequirements
GNU make, C++17
In Views
Databases , HighPerformanceComputing , MachineLearning , ModelDeployment , Survival
CRAN Checks
xgboost results
Reference Manual
xgboost.html , xgboost.pdf
Vignettes
XGBoost for R introduction ( source , R code ) XGBoost from JSON ( source , R code )
Package Source
xgboost_3.2.1.1.tar.gz
Windows Binaries
r-devel: xgboost_3.2.1.1.zip , r-release: xgboost_3.2.1.1.zip , r-oldrel: xgboost_3.2.1.1.zip
MacOS Binaries
r-release (arm64): xgboost_3.2.1.1.tgz , r-oldrel (arm64): xgboost_3.2.1.1.tgz , r-release (x86_64): xgboost_3.2.1.1.tgz , r-oldrel (x86_64): xgboost_3.2.1.1.tgz
Old Sources
xgboost archive
Reverse Depends
LogisticEnsembles , NumericEnsembles , PIE
Reverse Imports
adapt4pv , alookr , audrex , autoBagging , autostats , bambu , BayesSpace , BioMoR , BioPred , CausalGPS , CCI , cpfa , CRE , csmpv , CytoProfile , ddml , DSAM , DSWE , E2E , EFAfactors , EHRmuse , EIX , fastml , FastRet , fastrmodels , FoRecoML , funcml , ggscidca , glmnetr , GNET2 , HCPclust , IBLM , iimi , imanr , infinityFlow , irboost , IVDML , latentFactoR , ldmppr , LTFGRS , LTFHPlus , MAPFX , MBMethPred , MethScope , MFF , mikropml , mixgb , mlspatial , modeltime , nadir , nfl4th , nflfastR , nsga3 , personalized , PND.heter.cluster , postcard , PoweREST , predhy , predhy.GUI , predictoR , promor , qshap , quickSentiment , radiant.model , reddPrec , ReSurv , RFGeneRank , rminer , roseRF , scDblFinder , scds , scPOEM , SELF , SEMdeep , sentiment.ai , SHAPBoost , SHAPforxgboost , shapviz , simPop , SMMAL , survalis , surveyvoi , tidybins , tidysdm , traineR , TSCI , tsensembler , twang , utsf , VIM , wactor , weightedGCM , xgb2sql , xpect , xrf
Reverse Suggests
automatedRecLin , BAGofT , bigsnpr , bioLeak , biomod2 , BORG , breakDown , bundle , butcher , caretSDM , cfbfastR , CimpleG , ClassifyR , coefplot , comets , cornet , CrcBiomeScreen , cuda.ml , CytoMethIC , DALEXtra , daltoolbox , DeepLearningCausal , drape , e2tree , easyalluvial , embed , explore , familiar , fdm2id , FLAME , flevr , GenericML , h3sdm , interflex , lime , LLMAgentR , MachineShop , MantaID , marginaleffects , mcboost , miesmuschel , misl , mistyR , ml , mlflow , mllrnrs , mlr , mlr3benchmark , mlr3hyperband , mlr3learners , mlr3shiny , mlr3tuning , mlr3tuningspaces , mlr3viz , mlsurvlrnrs , MLwrap , modelStudio , modeltime.ensemble , MSclassifR , offsetreg , OpEnCAST , orbital , parsnip , pathMED , PatientLevelPrediction , pdp , PheCAP , pmml , polle , PortfolioTesteR , qeML , r2pmml , rattle , rBayesianOptimization , rush , sense , shapr , sits , stackgbm , SuperLearner , SuperSurv , survex , tabnet , targeted , tidylearn , tidypopgen , tidypredict , treeshap , tune , vetiver , vimp , vivid , XAItest
Reverse Enhances
fastshap , vip
Page sections 4
Documentation
Heading
Documentation
Links
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Text
Reference manual: xgboost.html , xgboost.pdf Vignettes: XGBoost for R introduction ( source , R code ) XGBoost from JSON ( source , R code )
Downloads
Heading
Downloads
Links
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Text
Package source: xgboost_3.2.1.1.tar.gz Windows binaries: r-devel: xgboost_3.2.1.1.zip , r-release: xgboost_3.2.1.1.zip , r-oldrel: xgboost_3.2.1.1.zip macOS binaries: r-release (arm64): xgboost_3.2.1.1.tgz , r-oldrel (arm64): xgboost_3.2.1.1.tgz , r-release (x86_64): xgboost_3.2.1.1.tgz , r-oldrel (x86_64): xgboost_3.2.1.1.tgz Old sources: xgboost archive
Reverse dependencies
Heading
Reverse dependencies
Links
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Text
Reverse depends: LogisticEnsembles , NumericEnsembles , PIE Reverse imports: adapt4pv , alookr , audrex , autoBagging , autostats , bambu , BayesSpace , BioMoR , BioPred , CausalGPS , CCI , cpfa , CRE , csmpv , CytoProfile , ddml , DSAM , DSWE , E2E , EFAfactors , EHRmuse , EIX , fastml , FastRet , fastrmodels , FoRecoML , funcml , ggscidca , glmnetr , GNET2 , HCPclust , IBLM , iimi , imanr , infinityFlow , irboost , IVDML , latentFactoR , ldmppr , LTFGRS , LTFHPlus , MAPFX , MBMethPred , MethScope , MFF , mikropml , mixgb , mlspatial , modeltime , nadir , nfl4th , nflfastR , nsga3 , personalized , PND.heter.cluster , postcard , PoweREST , predhy , predhy.GUI , predictoR , promor , qshap , quickSentiment , radiant.model , reddPrec , ReSurv , RFGeneRank , rminer , roseRF , scDblFinder , scds , scPOEM , SELF , SEMdeep , sentiment.ai , SHAPBoost , SHAPforxgboost , shapviz , simPop , SMMAL , survalis , surveyvoi , tidybins , tidysdm , traineR , TSCI , tsensembler , twang , utsf , VIM , wactor , weightedGCM , xgb2sql , xpect , xrf Reverse suggests: automatedRecLin , BAGofT , bigsnpr , bioLeak , biomod2 , BORG , breakDown , bundle , butcher , caretSDM , cfbfastR , CimpleG , ClassifyR , coefplot , comets , cornet , CrcBiomeScreen , cuda.ml , CytoMethIC , DALEXtra , daltoolbox , DeepLearningCausal , drape , e2tree , easyalluvial , embed , explore , familiar , fdm2id , FLAME , flevr , GenericML , h3sdm , interflex , lime , LLMAgentR , MachineShop , MantaID , marginaleffects , mcboost , miesmuschel , misl , mistyR , ml , mlflow , mllrnrs , mlr , mlr3benchmark , mlr3hyperband , mlr3learners , mlr3shiny , mlr3tuning , mlr3tuningspaces , mlr3viz , mlsurvlrnrs , MLwrap , modelStudio , modeltime.ensemble , MSclassifR , offsetreg , OpEnCAST , orbital , parsnip , pathMED , PatientLevelPrediction , pdp , PheCAP , pmml , polle , PortfolioTesteR , qeML , r2pmml , rattle , rBayesianOptimization , rush , sense , shapr , sits , stackgbm , SuperLearner , SuperSurv , survex , tabnet , targe
Linking
Heading
Linking
Links
[{"label":"https://CRAN.R-project.org/package=xgboost","section":"","type":"","url":"https://CRAN.R-project.org/package=xgboost"}]
Text
Please use the canonical form https://CRAN.R-project.org/package=xgboost to link to this page.
Documentation 8
Vignettes 6
Downloads 9
All page links 120

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RepositoryVersionPublishedFirst seenLast seenDocs
CRAN3.2.1.12026-05-292026-05-30

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