prepare.ggplot.shap.data |
Combine and melt feature values and SHAP contributions for sample
observations. |
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 |
cb.save.model |
Callback closure for saving a model file. |
print.xgb.cv.synchronous |
Print xgb.cv result |
print.xgb.DMatrix |
Print xgb.DMatrix |
cb.early.stop |
Callback closure to activate the early stopping. |
xgb.create.features |
Create new features from a previously learned model |
xgb.config |
Accessors for model parameters as JSON string. |
xgb.cv |
Cross Validation |
xgb.dump |
Dump an xgboost model in text format. |
xgb.model.dt.tree |
Parse a boosted tree model text dump |
xgb.parameters<- |
Accessors for model parameters. |
xgb.ggplot.deepness |
Plot model trees deepness |
xgb.ggplot.importance |
Plot feature importance as a bar graph |
predict.xgb.Booster |
Predict method for eXtreme Gradient Boosting model |
xgb.plot.multi.trees |
Project all trees on one tree and plot it |
normalize |
Scale feature value to have mean 0, standard deviation 1 |
xgb.DMatrix.save |
Save xgb.DMatrix object to binary file |
xgb.attr |
Accessors for serializable attributes of a model. |
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.shap.data |
Prepare data for SHAP plots. To be used in xgb.plot.shap, xgb.plot.shap.summary, etc.
Internal utility function. |
slice |
Get a new DMatrix containing the specified rows of
original xgb.DMatrix object |
setinfo |
Set information of an xgb.DMatrix object |
xgb.ggplot.shap.summary |
SHAP contribution dependency summary plot |
xgb.gblinear.history |
Extract gblinear coefficients history. |
xgb.plot.shap |
SHAP contribution dependency plots |
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.importance |
Importance of features in a model. |
xgb.load.raw |
Load serialised xgboost model from R's raw vector |
xgb.load |
Load xgboost model from binary file |
xgb.plot.tree |
Plot a boosted tree model |
xgb.DMatrix |
Construct xgb.DMatrix object |
print.xgb.Booster |
Print xgb.Booster |
xgb.train |
eXtreme Gradient Boosting Training |
xgb.unserialize |
Load the instance back from xgb.serialize |
xgb.Booster.complete |
Restore missing parts of an incomplete xgb.Booster object. |
xgboost-deprecated |
Deprecation notices. |
cb.cv.predict |
Callback closure for returning cross-validation based predictions. |
callbacks |
Callback closures for booster training. |
agaricus.train |
Training part from Mushroom Data Set |
agaricus.test |
Test part from Mushroom Data Set |
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. |
cb.print.evaluation |
Callback closure for printing the result of evaluation |
cb.gblinear.history |
Callback closure for collecting the model coefficients history of a gblinear booster
during its training. |
cb.reset.parameters |
Callback closure for resetting the booster's parameters at each iteration. |
cb.evaluation.log |
Callback closure for logging the evaluation history |
No Results! |