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
- Python API Reference
- Global Configuration
- Core Data Structure
DMatrix
DMatrix.feature_names
DMatrix.feature_types
DMatrix.get_base_margin()
DMatrix.get_float_info()
DMatrix.get_group()
DMatrix.get_label()
DMatrix.get_uint_info()
DMatrix.get_weight()
DMatrix.num_col()
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()
DeviceQuantileDMatrix
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.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
DaskDeviceQuantileDMatrix
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()
- Callback Functions
- Model
- XGBoost Python Feature Walkthrough
- XGBoost Dask Feature Walkthrough