R: Extreme Gradient Boosting

# Extreme Gradient Boosting

## Documentation for package ‘xgboost’ version 1.4.2.1

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

## Help Pages

a-compatibility-note-for-saveRDS-save | Do not use 'saveRDS' or 'save' for long-term archival of models. Instead, use 'xgb.save' or 'xgb.save.raw'.
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
normalize | Scale feature value to have mean 0, standard deviation 1
predict.xgb.Booster | Predict method for eXtreme Gradient Boosting model
predict.xgb.Booster.handle | Predict method for eXtreme Gradient Boosting model
prepare.ggplot.shap.data | Combine and melt feature values and SHAP contributions for sample observations.
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.config | Accessors for model parameters as JSON string.
xgb.config<- | Accessors for model parameters as JSON string.
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.get.config | Set and get global configuration
xgb.ggplot.deepness | Plot model trees deepness
xgb.ggplot.importance | Plot feature importance as a bar graph
xgb.ggplot.shap.summary | SHAP contribution dependency summary plot
xgb.importance | Importance of features in a model.
xgb.load | Load xgboost model from binary file
xgb.load.raw | Load serialised xgboost model from R's raw vector
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.shap.summary | SHAP contribution dependency summary plot
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.raw to load the model back from raw vector
xgb.serialize | Serialize the booster instance into R's raw vector. The serialization method differs from 'xgb.save.raw' as the latter one saves only the model but not parameters. This serialization format is not stable across different xgboost versions.
xgb.set.config | Set and get global configuration
xgb.set.config, xgb.get.config | Set and get global configuration
xgb.train | eXtreme Gradient Boosting Training
xgb.unserialize | Load the instance back from 'xgb.serialize'
xgboost | eXtreme Gradient Boosting Training
xgboost-deprecated | Deprecation notices.
[.xgb.DMatrix | Get a new DMatrix containing the specified rows of original xgb.DMatrix object