Man pages for xgboost
Extreme Gradient Boosting

a-compatibility-note-for-saveRDS-saveDo not use 'saveRDS' or 'save' for long-term archival of...
agaricus.testTest part from Mushroom Data Set
agaricus.trainTraining part from Mushroom Data Set
callbacksCallback closures for booster training. closure for returning cross-validation based...
cb.early.stopCallback closure to activate the early stopping.
cb.evaluation.logCallback closure for logging the evaluation history
cb.gblinear.historyCallback closure for collecting the model coefficients...
cb.print.evaluationCallback closure for printing the result of evaluation
cb.reset.parametersCallback closure for resetting the booster's parameters at... closure for saving a model file.
dimnames.xgb.DMatrixHandling of column names of 'xgb.DMatrix'
dim.xgb.DMatrixDimensions of xgb.DMatrix
getinfoGet information of an xgb.DMatrix object
predict.xgb.BoosterPredict method for eXtreme Gradient Boosting model
print.xgb.BoosterPrint xgb.Booster
print.xgb.cvPrint result
print.xgb.DMatrixPrint xgb.DMatrix
setinfoSet information of an xgb.DMatrix object
slice.xgb.DMatrixGet a new DMatrix containing the specified rows of original...
xgb.attrAccessors for serializable attributes of a model.
xgb.Booster.completeRestore missing parts of an incomplete xgb.Booster object.
xgb.configAccessors for model parameters as JSON string.
xgb.create.featuresCreate new features from a previously learned model
xgb.cvCross Validation
xgb.DMatrixConstruct xgb.DMatrix object
xgb.DMatrix.saveSave xgb.DMatrix object to binary file
xgb.dumpDump an xgboost model in text format.
xgb.gblinear.historyExtract gblinear coefficients history.
xgb.importanceImportance of features in a model.
xgb.loadLoad xgboost model from binary file
xgb.load.rawLoad serialised xgboost model from R's raw vector
xgb.model.dt.treeParse a boosted tree model text dump
xgboost-deprecatedDeprecation notices.
xgb.parametersAccessors for model parameters.
xgb.plot.deepnessPlot model trees deepness
xgb.plot.importancePlot feature importance as a bar graph
xgb.plot.multi.treesProject all trees on one tree and plot it
xgb.plot.shapSHAP contribution dependency plots
xgb.plot.treePlot a boosted tree model
xgb.saveSave xgboost model to binary file xgboost model to R's raw vector, user can call...
xgb.serializeSerialize the booster instance into R's raw vector. The...
xgb.traineXtreme Gradient Boosting Training
xgb.unserializeLoad the instance back from 'xgb.serialize'
xgboost documentation built on Sept. 2, 2020, 9:06 a.m.