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