ABSTRACT
Air pollution has become a threat to the lives of human, plants, and animal species. It's measured using the air quality index. Various air pollutants, such as carbon dioxide, carbon monoxide, particulate matter 2.5, and much more cause contamination of air. Therefore, it is beneficial to predict the air quality and make well-informed decisions to prevent any harm or effects. Multiple algorithms for machine learning have been devised and implemented to determine air quality index. This survey paper discusses several algorithms for machine learning that are used for predicting air quality. Machine-learning algorithms used are support vector machine, linear regression, artificial neural networks, decision tree, and random forest.
