Tag: XGBoost

Researchers have developed a focused positive-unlabeled learning method that uses focal loss to achieve state-of-the-art performance on severely imbalanced datasets ...

Researchers fused morphometric basin analysis with machine learning to map flood susceptibility across four Bayelsa State catchments, revealing hidden high-risk ...

A new Composite Degradation Index combining biomass trends and landscape fragmentation reveals that coniferous, broad-leaved, and mixed forests on the ...

A comparative study of more than 33,000 typhoon-triggered shallow landslides reveals that semi-humid northern China and humid southern China fail ...

A multi-level stacking ensemble of five machine learning models mapped porphyry copper-gold prospectivity in northwest Iran with an AUC of ...

Researchers in Porto have developed a game theory-inspired machine learning framework that gives each transportation mode its own tailored feature ...

A hybrid NARX–XGBoost machine learning framework predicts daily milk yields in heat-stressed dairy cows with substantially higher accuracy than existing ...

Researchers combined statistics, machine learning, and GIS to predict water quality in Dhaka's heavily polluted Turag River with over 90 ...

An Indian research team has combined a gold-coated photonic crystal fiber SPR sensor with a hybrid CNN-SVM-XGBoost framework that classifies ...

Researchers have developed an explainable multimodal machine-learning model that predicts with over 81 percent accuracy whether people with mild cognitive ...