Package index • xgboost

High Level Interface

High level XGBoost interface

xgboost(): Fit XGBoost Model
predict(<xgboost>): Compute predictions from XGBoost model on new data
print(<xgboost>): Print info from XGBoost model

Datasets

Test datasets bundled with the R package.

agaricus.train: Training part from Mushroom Data Set
agaricus.test: Test part from Mushroom Data Set

Global Configuration

Global configuration for the XGBoost library.

xgb.config() `xgb.config<-`(): Accessors for model parameters as JSON string
xgb.set.config() xgb.get.config(): Set and get global configuration

DMatrix

Low-level data storage.

xgb.DMatrix() xgb.QuantileDMatrix(): Construct xgb.DMatrix object
xgb.DMatrix.hasinfo(): Check whether DMatrix object has a field
xgb.DMatrix.save(): Save xgb.DMatrix object to binary file
dim(<xgb.DMatrix>): Dimensions of xgb.DMatrix
dimnames(<xgb.DMatrix>) `dimnames<-`(<xgb.DMatrix>): Handling of column names of xgb.DMatrix
print(<xgb.DMatrix>): Print xgb.DMatrix
xgb.DataBatch(): Structure for Data Batches
xgb.DataIter(): XGBoost Data Iterator
xgb.get.DMatrix.data(): Get DMatrix Data
xgb.get.DMatrix.num.non.missing(): Get Number of Non-Missing Entries in DMatrix
xgb.ExtMemDMatrix(): DMatrix from External Data
xgb.QuantileDMatrix.from_iterator(): QuantileDMatrix from External Data
xgb.get.DMatrix.qcut(): Get Quantile Cuts from DMatrix
xgb.slice.DMatrix() `[`(<xgb.DMatrix>): Slice DMatrix

Booster

The model for XGBoost.

a-compatibility-note-for-saveRDS-save: Model Serialization and Compatibility
coef(<xgb.Booster>): Extract coefficients from linear booster
getinfo() setinfo(): Get or set information of xgb.DMatrix and xgb.Booster objects
predict(<xgb.Booster>): Predict method for XGBoost model
print(<xgb.Booster>): Print xgb.Booster
xgb.load(): Load XGBoost model from binary file
xgb.load.raw(): Load serialised XGBoost model from R's raw vector
xgb.save(): Save XGBoost model to binary file
xgb.save.raw(): Save XGBoost model to R's raw vector
xgb.copy.Booster(): Deep-copies a Booster Object
xgb.slice.Booster() `[`(<xgb.Booster>): Slice Booster by Rounds
xgb.get.num.boosted.rounds() length(<xgb.Booster>): Get number of boosting in a fitted booster
xgb.is.same.Booster(): Check if two boosters share the same C object
xgb.importance(): Feature importance
xgb.attr() `xgb.attr<-`() xgb.attributes() `xgb.attributes<-`(): Accessors for serializable attributes of a model
xgb.create.features(): Create new features from a previously learned model
xgb.model.dt.tree(): Parse model text dump
`xgb.model.parameters<-`(): Accessors for model parameters
xgb.ggplot.deepness() xgb.plot.deepness(): Plot model tree depth
xgb.dump(): Dump an XGBoost model in text format.
variable.names(<xgb.Booster>): Get Features Names from Booster
xgb.ggplot.importance() xgb.plot.importance(): Plot feature importance
xgb.plot.multi.trees(): Project all trees on one tree
xgb.plot.shap(): SHAP dependence plots
xgb.ggplot.shap.summary() xgb.plot.shap.summary(): SHAP summary plot
xgb.plot.tree(): Plot boosted trees
xgb.gblinear.history(): Extract gblinear coefficients history

Training Callbacks

Callback functions used for training.

xgb.Callback(): XGBoost Callback Constructor
xgb.cb.cv.predict(): Callback for returning cross-validation based predictions
xgb.cb.early.stop(): Callback to activate early stopping
xgb.cb.evaluation.log(): Callback for logging the evaluation history
xgb.cb.gblinear.history(): Callback for collecting coefficients history of a gblinear booster
xgb.cb.print.evaluation(): Callback for printing the result of evaluation
xgb.cb.reset.parameters(): Callback for resetting booster parameters at each iteration
xgb.cb.save.model(): Callback for saving a model file

Low-level Training Functions

Low-level Training Functions with DMatrix and Booster

xgb.params(): XGBoost Parameters
xgb.train(): Fit XGBoost Model
xgb.cv(): Cross Validation
print(<xgb.cv.synchronous>): Print xgb.cv result

Deprecation Settings

xgboost-options: XGBoost Options