R: Extreme Gradient Boosting

# Extreme Gradient Boosting

## Documentation for package ‘xgboost’ version 0.82.0.1

- DESCRIPTION file.
- Code demos. Use demo() to run them.

## Help Pages

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.gblinear.history | Callback closure for collecting the model coefficients history of a gblinear booster during its training.
cb.print.evaluation | Callback closure for printing the result of evaluation
cb.reset.parameters | Callback closure for resetting 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'
dimnames<-.xgb.DMatrix | Handling of column names of 'xgb.DMatrix'
getinfo | Get information of an xgb.DMatrix object
getinfo.xgb.DMatrix | Get information of an xgb.DMatrix object
predict.xgb.Booster | Predict method for eXtreme Gradient Boosting model
predict.xgb.Booster.handle | Predict method for eXtreme Gradient Boosting model
print.xgb.Booster | Print xgb.Booster
print.xgb.cv.synchronous | Print xgb.cv result
print.xgb.DMatrix | Print xgb.DMatrix
setinfo | Set information of an xgb.DMatrix object
setinfo.xgb.DMatrix | Set information of an xgb.DMatrix object
slice | Get a new DMatrix containing the specified rows of original xgb.DMatrix object
slice.xgb.DMatrix | Get a new DMatrix containing the specified rows of original xgb.DMatrix object
xgb.attr | Accessors for serializable attributes of a model.
xgb.attr<- | Accessors for serializable attributes of a model.
xgb.attributes | Accessors for serializable attributes of a model.
xgb.attributes<- | Accessors for serializable attributes of a model.
xgb.Booster.complete | Restore missing parts of an incomplete xgb.Booster object.
xgb.create.features | Create new features from a previously learned model
xgb.cv | Cross Validation
xgb.DMatrix | Construct xgb.DMatrix object
xgb.DMatrix.save | Save xgb.DMatrix object to binary file
xgb.dump | Dump an xgboost model in text format.
xgb.gblinear.history | Extract gblinear coefficients history.
xgb.ggplot.deepness | Plot model trees deepness
xgb.ggplot.importance | Plot feature importance as a bar graph
xgb.importance | 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.deepness | Plot model trees deepness
xgb.plot.importance | Plot feature importance as a bar graph
xgb.plot.multi.trees | Project all trees on one tree and plot it
xgb.plot.shap | SHAP contribution dependency plots
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 | eXtreme Gradient Boosting Training
xgboost-deprecated | Deprecation notices.
[.xgb.DMatrix | Get a new DMatrix containing the specified rows of original xgb.DMatrix object