XGBoost
Cross-source consensus on XGBoost from 1 sources and 4 claims.
1 sources · 4 claims
How it works
Risks & contraindications
Comparisons
Highlighted claims
- XGBoost performed best among the tested regression methods and was selected for the final models. — Prediction of Oswestry Disability Index and Numeric Rating Scale scores after lumbar spine surgery: machine learning model development and fairness assessment
- The final models clipped predictions outside the valid ODI and NRS ranges. — Prediction of Oswestry Disability Index and Numeric Rating Scale scores after lumbar spine surgery: machine learning model development and fairness assessment
- The study selected 22 predictors after SHAP analysis and expert review for clinical relevance and legality. — Prediction of Oswestry Disability Index and Numeric Rating Scale scores after lumbar spine surgery: machine learning model development and fairness assessment
- XGBoost was described as suitable for structured data but requiring hyperparameter tuning to reduce overfitting risk. — Prediction of Oswestry Disability Index and Numeric Rating Scale scores after lumbar spine surgery: machine learning model development and fairness assessment