Tag: XGBoost

A machine learning framework trained on more than 13,000 granite samples classifies tectonic settings with 91 percent accuracy while SHAP ...

Brazilian researchers used machine learning and Shapley values to predict which non-native plants in the Caatinga dry forest will become ...

Researchers in Vietnam have trained machine learning models on time-lapse morphokinetic data to predict live birth from CAPA-IVM embryos, achieving ...

A field-validated system combining drone multispectral imaging, explainable XGBoost AI, and edge-controlled variable-rate application cut nitrogen fertilizer use by 21.8 ...

A new machine learning framework trained on roughly 434,000 nonlinear earthquake simulations reveals that taller steel buildings need proportionally fewer ...

A machine learning framework that designs its own experiments boosted diacylglycerol yield from sunflower oil and cut prediction error fourteenfold ...

Researchers compiled 32,714 landslide records and built a selective ensemble machine learning framework that stabilizes runout distance prediction and reveals ...

A new event-based machine learning approach reframes vineyard mildew forecasting as the prediction of disease-risk episodes rather than daily status ...

A hybrid XGBoost-based machine learning framework has distilled Crohn's disease risk prediction down to just 15 genetic variants, achieving over ...

Researchers in India and Spain show that ensemble machine learning models combined with explainable AI can detect causal relationships in ...