Man pages for xgboost
Extreme Gradient Boosting
| a-compatibility-note-for-saveRDS-save | Do not use 'saveRDS' or 'save' for long-term archival of... |
| 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... |
| 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... |
| cb.print.evaluation | Callback closure for printing the result of evaluation |
| cb.reset.parameters | Callback closure for resetting the booster's parameters at... |
| cb.save.model | Callback closure for saving a model file. |
| dimnames.xgb.DMatrix | Handling of column names of 'xgb.DMatrix' |
| dim.xgb.DMatrix | Dimensions of xgb.DMatrix |
| getinfo | 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 |
| prepare.ggplot.shap.data | Combine and melt feature values and SHAP contributions for... |
| print.xgb.Booster | Print xgb.Booster |
| print.xgb.cv | Print xgb.cv result |
| print.xgb.DMatrix | Print xgb.DMatrix |
| setinfo | Set information of an xgb.DMatrix object |
| slice.xgb.DMatrix | Get a new DMatrix containing the specified rows of original... |
| xgb.attr | 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. |
| xgbConfig | Set and get global configuration |
| 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.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 |
| xgboost-deprecated | Deprecation notices. |
| 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.serialize | Serialize the booster instance into R's raw vector. The... |
| xgb.shap.data | Prepare data for SHAP plots. To be used in xgb.plot.shap,... |
| xgb.train | eXtreme Gradient Boosting Training |
| xgb.unserialize | Load the instance back from 'xgb.serialize' |
