Tag: XGBoost

A new benchmark finds that prompt-engineered contextual embeddings improved Random Forest but failed to outperform a strong tabular XGBoost model ...

A systematic review of 78 papers examines how machine learning methods support demand forecasting and inventory decision-making.

A retrospective single-center study of 487 patients developed interpretable machine learning models that predict gangrenous cholecystitis before surgery using five ...

A computational study combined gene co-expression network analysis and machine learning to nominate twelve candidate biomarkers for malignant pleural mesothelioma, ...

A machine learning framework combining multi-temporal lidar and satellite data mapped post-fire debris flows across seven Oregon watersheds, with multi-temporal ...

An integrated experimental and machine learning study predicted the 28-day compressive strength of recycled aggregate concrete, with Support Vector Regression ...

A new attention-based neural network that reconfigures its risk logic according to macroeconomic conditions outperformed standard machine learning and statistical ...

A UK Biobank study of nearly 400,000 adults found that higher triglyceride-glucose index values, especially when combined with waist measurements, ...

A PSO-optimized XGBoost model predicted the compressive strength, elastic energy index and impact energy index of gangue-cemented backfill materials with ...

Researchers trained a machine learning surrogate on 120 simulations that predicts WAAM thermal histories in milliseconds and calibrates uncertain model ...