Extreme Gradient Boosting


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Documentation for package ‘xgboost’ version 1.7.7.1

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