Package: xgboost 1.7.8.1
xgboost: Extreme Gradient Boosting
Extreme Gradient Boosting, which is an efficient implementation of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>. This package is its R interface. The package includes efficient linear model solver and tree learning algorithms. The package can automatically do parallel computation on a single machine which could be more than 10 times faster than existing gradient boosting packages. It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that users are also allowed to define their own objectives easily.
Authors:
xgboost_1.7.8.1.tar.gz
xgboost_1.7.8.1.tar.gz(r-4.5-noble)xgboost_1.7.8.1.tar.gz(r-4.4-noble)
xgboost.pdf |xgboost.html✨
xgboost/json (API)
# Install 'xgboost' in R: |
install.packages('xgboost', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dmlc/xgboost/issues
- agaricus.test - Test part from Mushroom Data Set
- agaricus.train - Training part from Mushroom Data Set
Last updated 2 months agofrom:0e3a1fd399. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Aug 24 2024 |
R-4.5-linux-x86_64 | NOTE | Aug 24 2024 |
Exports:cb.cv.predictcb.early.stopcb.evaluation.logcb.gblinear.historycb.print.evaluationcb.reset.parameterscb.save.modelgetinfosetinfoslicexgb.attrxgb.attr<-xgb.attributesxgb.attributes<-xgb.Booster.completexgb.configxgb.config<-xgb.create.featuresxgb.cvxgb.DMatrixxgb.DMatrix.savexgb.dumpxgb.gblinear.historyxgb.get.configxgb.ggplot.deepnessxgb.ggplot.importancexgb.ggplot.shap.summaryxgb.importancexgb.loadxgb.load.rawxgb.model.dt.treexgb.parameters<-xgb.plot.deepnessxgb.plot.importancexgb.plot.multi.treesxgb.plot.shapxgb.plot.shap.summaryxgb.plot.treexgb.savexgb.save.rawxgb.serializexgb.set.configxgb.trainxgb.unserializexgboost
Dependencies:data.tablejsonlitelatticeMatrix
Understand your dataset with XGBoost
Rendered fromdiscoverYourData.Rmd
usingknitr::rmarkdown
on Aug 24 2024.Last update: 2024-07-25
Started: 2015-03-03
XGBoost from JSON
Rendered fromxgboostfromJSON.Rmd
usingknitr::rmarkdown
on Aug 24 2024.Last update: 2023-12-07
Started: 2019-07-25
XGBoost presentation
Rendered fromxgboostPresentation.Rmd
usingknitr::rmarkdown
on Aug 24 2024.Last update: 2024-07-25
Started: 2015-03-03
xgboost: eXtreme Gradient Boosting
Rendered fromxgboost.Rnw
usingknitr::knitr
on Aug 24 2024.Last update: 2024-07-25
Started: 2014-09-01