Tag: XGBoost

Researchers used SHAP-based explainable AI to identify a single EEG electrode and just seven features that detect virtual reality motion ...

A new study combines hydrological simulation, machine learning and spatial statistics to rank flood risk for 5,482 historic buildings across ...

Researchers at the University of Gondar report that a voting ensemble of tree-based machine learning models combined with permutation-based feature ...

A new architecture-diverse TabNet ensemble classifies seven crop types from harmonized multi-source soil data with 90.5 percent accuracy, outperforming XGBoost ...

A leakage-controlled machine learning framework converts heterogeneous European emission products into metal-specific datasets, achieving high accuracy for cadmium, mercury, and ...

A hybrid multilevel and machine learning analysis of Ghana's 2022 Demographic and Health Survey identifies nine high-confidence predictors of childhood ...

A new study tests whether trade, governance and environmental tax indicators can classify national CO2 emission levels, and finds that ...

A sentinel hospital study in Guangzhou tested a reporting-lag-aware machine learning framework for seven-day-ahead forecasting of influenza, COVID-19 and Mycoplasma ...

An interpretable machine learning model trained on European injury surveillance data can identify emergency department patients whose records show documented ...

Researchers at Vellore Institute of Technology have developed TOAD-ML, a machine learning framework that validates decentralized finance oracle price feeds ...