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Helpful examples for improving the performance of XGBoost models (e.g. reduce execution time or memory usage during training).

Speed-Up XGBoost (Reduce Execution Time)
XGBClassifier Faster Than CatBoostClassifier
XGBClassifier Faster Than GradientBoostingClassifier
XGBClassifier Faster Than HistGradientBoostingClassifier
XGBClassifier Faster Than LGBMClassifier
XGBoost Benchmark Model Training Time
XGBoost Configure "OMP_NUM_THREADS" for Inference
XGBoost Configure "OMP_NUM_THREADS" for Model Training
XGBoost CPU Usage Below 100% During Training
XGBoost Native Categorical Faster Than One Hot and Ordinal Encoding
XGBoost Releases GIL During Inference (prediction)
XGBoost Releases GIL During Training
XGBoost Releases the Global Interpreter Lock (GIL)
XGBoost Report Execution Time
XGBoost Training Time of Max Depth vs Boosting Rounds
XGBoost Training Time of Threads vs Boosting Rounds
XGBoost Training Time of Tree Method vs Boosting Rounds
XGBoost Use Less Memory
XGBRegressor faster than CatBoostRegressor
XGBRegressor Faster Than GradientBoostingRegressor
XGBRegressor Faster Than HistGradientBoostingRegressor
XGBRegressor Faster Than LGBMRegressor
XGBRFClassifier Faster Than RandomForestClassifier
XGBRFRegressor Faster Than RandomForestRegressor