XGBoost Python Package
This page contains links to all the python related documents on python package. To install the package, checkout Installation Guide.
Contents
- Python Package Introduction
- Using the Scikit-Learn Estimator Interface
- Python API Reference
- Global Configuration
- Core Data Structure
DMatrix
DMatrix.feature_names
DMatrix.feature_types
DMatrix.get_base_margin()
DMatrix.get_data()
DMatrix.get_float_info()
DMatrix.get_group()
DMatrix.get_label()
DMatrix.get_uint_info()
DMatrix.get_weight()
DMatrix.num_col()
DMatrix.num_nonmissing()
DMatrix.num_row()
DMatrix.save_binary()
DMatrix.set_base_margin()
DMatrix.set_float_info()
DMatrix.set_float_info_npy2d()
DMatrix.set_group()
DMatrix.set_info()
DMatrix.set_label()
DMatrix.set_uint_info()
DMatrix.set_weight()
DMatrix.slice()
QuantileDMatrix
Booster
Booster.attr()
Booster.attributes()
Booster.boost()
Booster.copy()
Booster.dump_model()
Booster.eval()
Booster.eval_set()
Booster.feature_names
Booster.feature_types
Booster.get_dump()
Booster.get_fscore()
Booster.get_score()
Booster.get_split_value_histogram()
Booster.inplace_predict()
Booster.load_config()
Booster.load_model()
Booster.num_boosted_rounds()
Booster.num_features()
Booster.predict()
Booster.save_config()
Booster.save_model()
Booster.save_raw()
Booster.set_attr()
Booster.set_param()
Booster.trees_to_dataframe()
Booster.update()
- Learning API
- Scikit-Learn API
XGBRegressor
XGBRegressor.apply()
XGBRegressor.best_iteration
XGBRegressor.best_score
XGBRegressor.coef_
XGBRegressor.evals_result()
XGBRegressor.feature_importances_
XGBRegressor.feature_names_in_
XGBRegressor.fit()
XGBRegressor.get_booster()
XGBRegressor.get_num_boosting_rounds()
XGBRegressor.get_params()
XGBRegressor.get_xgb_params()
XGBRegressor.intercept_
XGBRegressor.load_model()
XGBRegressor.n_features_in_
XGBRegressor.predict()
XGBRegressor.save_model()
XGBRegressor.score()
XGBRegressor.set_params()
XGBClassifier
XGBClassifier.apply()
XGBClassifier.best_iteration
XGBClassifier.best_score
XGBClassifier.coef_
XGBClassifier.evals_result()
XGBClassifier.feature_importances_
XGBClassifier.feature_names_in_
XGBClassifier.fit()
XGBClassifier.get_booster()
XGBClassifier.get_num_boosting_rounds()
XGBClassifier.get_params()
XGBClassifier.get_xgb_params()
XGBClassifier.intercept_
XGBClassifier.load_model()
XGBClassifier.n_features_in_
XGBClassifier.predict()
XGBClassifier.predict_proba()
XGBClassifier.save_model()
XGBClassifier.score()
XGBClassifier.set_params()
XGBRanker
XGBRanker.apply()
XGBRanker.best_iteration
XGBRanker.best_score
XGBRanker.coef_
XGBRanker.evals_result()
XGBRanker.feature_importances_
XGBRanker.feature_names_in_
XGBRanker.fit()
XGBRanker.get_booster()
XGBRanker.get_num_boosting_rounds()
XGBRanker.get_params()
XGBRanker.get_xgb_params()
XGBRanker.intercept_
XGBRanker.load_model()
XGBRanker.n_features_in_
XGBRanker.predict()
XGBRanker.save_model()
XGBRanker.score()
XGBRanker.set_params()
XGBRFRegressor
XGBRFRegressor.apply()
XGBRFRegressor.best_iteration
XGBRFRegressor.best_score
XGBRFRegressor.coef_
XGBRFRegressor.evals_result()
XGBRFRegressor.feature_importances_
XGBRFRegressor.feature_names_in_
XGBRFRegressor.fit()
XGBRFRegressor.get_booster()
XGBRFRegressor.get_num_boosting_rounds()
XGBRFRegressor.get_params()
XGBRFRegressor.get_xgb_params()
XGBRFRegressor.intercept_
XGBRFRegressor.load_model()
XGBRFRegressor.n_features_in_
XGBRFRegressor.predict()
XGBRFRegressor.save_model()
XGBRFRegressor.score()
XGBRFRegressor.set_params()
XGBRFClassifier
XGBRFClassifier.apply()
XGBRFClassifier.best_iteration
XGBRFClassifier.best_score
XGBRFClassifier.coef_
XGBRFClassifier.evals_result()
XGBRFClassifier.feature_importances_
XGBRFClassifier.feature_names_in_
XGBRFClassifier.fit()
XGBRFClassifier.get_booster()
XGBRFClassifier.get_num_boosting_rounds()
XGBRFClassifier.get_params()
XGBRFClassifier.get_xgb_params()
XGBRFClassifier.intercept_
XGBRFClassifier.load_model()
XGBRFClassifier.n_features_in_
XGBRFClassifier.predict()
XGBRFClassifier.predict_proba()
XGBRFClassifier.save_model()
XGBRFClassifier.score()
XGBRFClassifier.set_params()
- Plotting API
- Callback API
- Dask API
- Dask extensions for distributed training
DaskDMatrix
DaskQuantileDMatrix
train()
predict()
inplace_predict()
DaskXGBClassifier
DaskXGBClassifier.apply()
DaskXGBClassifier.best_iteration
DaskXGBClassifier.best_score
DaskXGBClassifier.client
DaskXGBClassifier.coef_
DaskXGBClassifier.evals_result()
DaskXGBClassifier.feature_importances_
DaskXGBClassifier.feature_names_in_
DaskXGBClassifier.fit()
DaskXGBClassifier.get_booster()
DaskXGBClassifier.get_num_boosting_rounds()
DaskXGBClassifier.get_params()
DaskXGBClassifier.get_xgb_params()
DaskXGBClassifier.intercept_
DaskXGBClassifier.load_model()
DaskXGBClassifier.n_features_in_
DaskXGBClassifier.predict()
DaskXGBClassifier.predict_proba()
DaskXGBClassifier.save_model()
DaskXGBClassifier.score()
DaskXGBClassifier.set_params()
DaskXGBRegressor
DaskXGBRegressor.apply()
DaskXGBRegressor.best_iteration
DaskXGBRegressor.best_score
DaskXGBRegressor.client
DaskXGBRegressor.coef_
DaskXGBRegressor.evals_result()
DaskXGBRegressor.feature_importances_
DaskXGBRegressor.feature_names_in_
DaskXGBRegressor.fit()
DaskXGBRegressor.get_booster()
DaskXGBRegressor.get_num_boosting_rounds()
DaskXGBRegressor.get_params()
DaskXGBRegressor.get_xgb_params()
DaskXGBRegressor.intercept_
DaskXGBRegressor.load_model()
DaskXGBRegressor.n_features_in_
DaskXGBRegressor.predict()
DaskXGBRegressor.save_model()
DaskXGBRegressor.score()
DaskXGBRegressor.set_params()
DaskXGBRanker
DaskXGBRanker.apply()
DaskXGBRanker.best_iteration
DaskXGBRanker.best_score
DaskXGBRanker.client
DaskXGBRanker.coef_
DaskXGBRanker.evals_result()
DaskXGBRanker.feature_importances_
DaskXGBRanker.feature_names_in_
DaskXGBRanker.fit()
DaskXGBRanker.get_booster()
DaskXGBRanker.get_num_boosting_rounds()
DaskXGBRanker.get_params()
DaskXGBRanker.get_xgb_params()
DaskXGBRanker.intercept_
DaskXGBRanker.load_model()
DaskXGBRanker.n_features_in_
DaskXGBRanker.predict()
DaskXGBRanker.save_model()
DaskXGBRanker.set_params()
DaskXGBRFRegressor
DaskXGBRFRegressor.apply()
DaskXGBRFRegressor.best_iteration
DaskXGBRFRegressor.best_score
DaskXGBRFRegressor.client
DaskXGBRFRegressor.coef_
DaskXGBRFRegressor.evals_result()
DaskXGBRFRegressor.feature_importances_
DaskXGBRFRegressor.feature_names_in_
DaskXGBRFRegressor.fit()
DaskXGBRFRegressor.get_booster()
DaskXGBRFRegressor.get_num_boosting_rounds()
DaskXGBRFRegressor.get_params()
DaskXGBRFRegressor.get_xgb_params()
DaskXGBRFRegressor.intercept_
DaskXGBRFRegressor.load_model()
DaskXGBRFRegressor.n_features_in_
DaskXGBRFRegressor.predict()
DaskXGBRFRegressor.save_model()
DaskXGBRFRegressor.score()
DaskXGBRFRegressor.set_params()
DaskXGBRFClassifier
DaskXGBRFClassifier.apply()
DaskXGBRFClassifier.best_iteration
DaskXGBRFClassifier.best_score
DaskXGBRFClassifier.client
DaskXGBRFClassifier.coef_
DaskXGBRFClassifier.evals_result()
DaskXGBRFClassifier.feature_importances_
DaskXGBRFClassifier.feature_names_in_
DaskXGBRFClassifier.fit()
DaskXGBRFClassifier.get_booster()
DaskXGBRFClassifier.get_num_boosting_rounds()
DaskXGBRFClassifier.get_params()
DaskXGBRFClassifier.get_xgb_params()
DaskXGBRFClassifier.intercept_
DaskXGBRFClassifier.load_model()
DaskXGBRFClassifier.n_features_in_
DaskXGBRFClassifier.predict()
DaskXGBRFClassifier.predict_proba()
DaskXGBRFClassifier.save_model()
DaskXGBRFClassifier.score()
DaskXGBRFClassifier.set_params()
- PySpark API
SparkXGBClassifier
SparkXGBClassifier.clear()
SparkXGBClassifier.copy()
SparkXGBClassifier.explainParam()
SparkXGBClassifier.explainParams()
SparkXGBClassifier.extractParamMap()
SparkXGBClassifier.fit()
SparkXGBClassifier.fitMultiple()
SparkXGBClassifier.getFeaturesCol()
SparkXGBClassifier.getLabelCol()
SparkXGBClassifier.getOrDefault()
SparkXGBClassifier.getParam()
SparkXGBClassifier.getPredictionCol()
SparkXGBClassifier.getProbabilityCol()
SparkXGBClassifier.getRawPredictionCol()
SparkXGBClassifier.getValidationIndicatorCol()
SparkXGBClassifier.getWeightCol()
SparkXGBClassifier.hasDefault()
SparkXGBClassifier.hasParam()
SparkXGBClassifier.isDefined()
SparkXGBClassifier.isSet()
SparkXGBClassifier.load()
SparkXGBClassifier.params
SparkXGBClassifier.read()
SparkXGBClassifier.save()
SparkXGBClassifier.set()
SparkXGBClassifier.setParams()
SparkXGBClassifier.uid
SparkXGBClassifier.write()
SparkXGBClassifierModel
SparkXGBClassifierModel.clear()
SparkXGBClassifierModel.copy()
SparkXGBClassifierModel.explainParam()
SparkXGBClassifierModel.explainParams()
SparkXGBClassifierModel.extractParamMap()
SparkXGBClassifierModel.getFeaturesCol()
SparkXGBClassifierModel.getLabelCol()
SparkXGBClassifierModel.getOrDefault()
SparkXGBClassifierModel.getParam()
SparkXGBClassifierModel.getPredictionCol()
SparkXGBClassifierModel.getProbabilityCol()
SparkXGBClassifierModel.getRawPredictionCol()
SparkXGBClassifierModel.getValidationIndicatorCol()
SparkXGBClassifierModel.getWeightCol()
SparkXGBClassifierModel.get_booster()
SparkXGBClassifierModel.get_feature_importances()
SparkXGBClassifierModel.hasDefault()
SparkXGBClassifierModel.hasParam()
SparkXGBClassifierModel.isDefined()
SparkXGBClassifierModel.isSet()
SparkXGBClassifierModel.load()
SparkXGBClassifierModel.params
SparkXGBClassifierModel.read()
SparkXGBClassifierModel.save()
SparkXGBClassifierModel.set()
SparkXGBClassifierModel.transform()
SparkXGBClassifierModel.uid
SparkXGBClassifierModel.write()
SparkXGBRegressor
SparkXGBRegressor.clear()
SparkXGBRegressor.copy()
SparkXGBRegressor.explainParam()
SparkXGBRegressor.explainParams()
SparkXGBRegressor.extractParamMap()
SparkXGBRegressor.fit()
SparkXGBRegressor.fitMultiple()
SparkXGBRegressor.getFeaturesCol()
SparkXGBRegressor.getLabelCol()
SparkXGBRegressor.getOrDefault()
SparkXGBRegressor.getParam()
SparkXGBRegressor.getPredictionCol()
SparkXGBRegressor.getValidationIndicatorCol()
SparkXGBRegressor.getWeightCol()
SparkXGBRegressor.hasDefault()
SparkXGBRegressor.hasParam()
SparkXGBRegressor.isDefined()
SparkXGBRegressor.isSet()
SparkXGBRegressor.load()
SparkXGBRegressor.params
SparkXGBRegressor.read()
SparkXGBRegressor.save()
SparkXGBRegressor.set()
SparkXGBRegressor.setParams()
SparkXGBRegressor.uid
SparkXGBRegressor.write()
SparkXGBRegressorModel
SparkXGBRegressorModel.clear()
SparkXGBRegressorModel.copy()
SparkXGBRegressorModel.explainParam()
SparkXGBRegressorModel.explainParams()
SparkXGBRegressorModel.extractParamMap()
SparkXGBRegressorModel.getFeaturesCol()
SparkXGBRegressorModel.getLabelCol()
SparkXGBRegressorModel.getOrDefault()
SparkXGBRegressorModel.getParam()
SparkXGBRegressorModel.getPredictionCol()
SparkXGBRegressorModel.getValidationIndicatorCol()
SparkXGBRegressorModel.getWeightCol()
SparkXGBRegressorModel.get_booster()
SparkXGBRegressorModel.get_feature_importances()
SparkXGBRegressorModel.hasDefault()
SparkXGBRegressorModel.hasParam()
SparkXGBRegressorModel.isDefined()
SparkXGBRegressorModel.isSet()
SparkXGBRegressorModel.load()
SparkXGBRegressorModel.params
SparkXGBRegressorModel.read()
SparkXGBRegressorModel.save()
SparkXGBRegressorModel.set()
SparkXGBRegressorModel.transform()
SparkXGBRegressorModel.uid
SparkXGBRegressorModel.write()
SparkXGBRanker
SparkXGBRanker.clear()
SparkXGBRanker.copy()
SparkXGBRanker.explainParam()
SparkXGBRanker.explainParams()
SparkXGBRanker.extractParamMap()
SparkXGBRanker.fit()
SparkXGBRanker.fitMultiple()
SparkXGBRanker.getFeaturesCol()
SparkXGBRanker.getLabelCol()
SparkXGBRanker.getOrDefault()
SparkXGBRanker.getParam()
SparkXGBRanker.getPredictionCol()
SparkXGBRanker.getValidationIndicatorCol()
SparkXGBRanker.getWeightCol()
SparkXGBRanker.hasDefault()
SparkXGBRanker.hasParam()
SparkXGBRanker.isDefined()
SparkXGBRanker.isSet()
SparkXGBRanker.load()
SparkXGBRanker.params
SparkXGBRanker.read()
SparkXGBRanker.save()
SparkXGBRanker.set()
SparkXGBRanker.setParams()
SparkXGBRanker.uid
SparkXGBRanker.write()
SparkXGBRankerModel
SparkXGBRankerModel.clear()
SparkXGBRankerModel.copy()
SparkXGBRankerModel.explainParam()
SparkXGBRankerModel.explainParams()
SparkXGBRankerModel.extractParamMap()
SparkXGBRankerModel.getFeaturesCol()
SparkXGBRankerModel.getLabelCol()
SparkXGBRankerModel.getOrDefault()
SparkXGBRankerModel.getParam()
SparkXGBRankerModel.getPredictionCol()
SparkXGBRankerModel.getValidationIndicatorCol()
SparkXGBRankerModel.getWeightCol()
SparkXGBRankerModel.get_booster()
SparkXGBRankerModel.get_feature_importances()
SparkXGBRankerModel.hasDefault()
SparkXGBRankerModel.hasParam()
SparkXGBRankerModel.isDefined()
SparkXGBRankerModel.isSet()
SparkXGBRankerModel.load()
SparkXGBRankerModel.params
SparkXGBRankerModel.read()
SparkXGBRankerModel.save()
SparkXGBRankerModel.set()
SparkXGBRankerModel.transform()
SparkXGBRankerModel.uid
SparkXGBRankerModel.write()
- Callback Functions
- Model
- XGBoost Python Feature Walkthrough
- XGBoost Dask Feature Walkthrough
- Survival Analysis Walkthrough