agaricus.test           Test part from Mushroom Data Set
agaricus.train          Training part from Mushroom Data Set
callbacks               Callback closures for booster training.
cb.cv.predict           Callback closure for returning cross-validation
                        based predictions.
cb.early.stop           Callback closure to activate the early
                        stopping.
cb.evaluation.log       Callback closure for logging the evaluation
                        history
cb.print.evaluation     Callback closure for printing the result of
                        evaluation
cb.reset.parameters     Callback closure for restetting the booster's
                        parameters at each iteration.
cb.save.model           Callback closure for saving a model file.
dim.xgb.DMatrix         Dimensions of xgb.DMatrix
dimnames.xgb.DMatrix    Handling of column names of 'xgb.DMatrix'
getinfo                 Get information of an xgb.DMatrix object
predict.xgb.Booster     Predict method for eXtreme Gradient Boosting
                        model
print.xgb.Booster       Print xgb.Booster
print.xgb.DMatrix       Print xgb.DMatrix
print.xgb.cv.synchronous
                        Print xgb.cv result
setinfo                 Set information of an xgb.DMatrix object
slice                   Get a new DMatrix containing the specified rows
                        of orginal xgb.DMatrix object
xgb.DMatrix             Contruct xgb.DMatrix object
xgb.DMatrix.save        Save xgb.DMatrix object to binary file
xgb.attr                Accessors for serializable attributes of a
                        model.
xgb.create.features     Create new features from a previously learned
                        model
xgb.cv                  Cross Validation
xgb.dump                Save xgboost model to text file
xgb.ggplot.deepness     Plot model trees deepness
xgb.ggplot.importance   Plot feature importance as a bar graph
xgb.importance          Show importance of features in a model
xgb.load                Load xgboost model from binary file
xgb.model.dt.tree       Parse a boosted tree model text dump
xgb.parameters<-        Accessors for model parameters.
xgb.plot.multi.trees    Project all trees on one tree and plot it
xgb.plot.tree           Plot a boosted tree model
xgb.save                Save xgboost model to binary file
xgb.save.raw            Save xgboost model to R's raw vector, user can
                        call xgb.load to load the model back from raw
                        vector
xgb.train               eXtreme Gradient Boosting Training
xgboost-deprecated      Deprecation notices.
