Machine Learning Models for daily AQI Prediction: An In-depth Analysis

The increase in pollutant concentrations in the atmosphere is one of the most important environmental challenges that must be addressed. Researchers employed a range of cutting- edge machine learning prediction algorithms to anticipate pollution. This study contrasts four different daily AQI pre- diction algorithms: Extra Tree Regressor, Random Forest Regressor, Light Gradient Boosting Machine and K-Nearest Neighbor. The assessment criteria used in this work to evaluate the models are RMSE, MAE and MAPE.