Ensemble learning for air quality index prediction: integrating gradient boosting, XGBoost, and stacking with SHAP-based interpretability

Abstract The increasing challenge of air pollution in cities requires smart methods to make proper predictions and manage the problem. Although machine learning and deep learning models have contributed greatly to weather and pollution forecasting, the main issue is the real-time flexibility, and sc...

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Autori principali:	Sukhendra Singh, Manoj Kumar, Vishal Sengar, Abhay Kumar, Kumar Abhishek, B. M. Ahamed Shafeeq
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Nature Portfolio 2026-02-01
Serie:	Scientific Reports
Soggetti:	Air quality index (AQI) Ensemble learning Feature engineering Gradient boosting Machine learning Predictive modeling
Accesso online:	https://doi.org/10.1038/s41598-026-39232-w
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