A Comparative Evaluation of Machine Learning Approaches for estimating Air Quality
DOI:
https://doi.org/10.7492/tf9t3238Keywords:
Air Quality, Machine Learning, Data Balancing, SMOTE, AdaboostAbstract
Air quality is critically important for the purpose of preserving a fresh environment, preventing ailments, and ensuring good health. It describes the extent of air pollution or cleanliness, which is determined by the concentrations of hazardous compounds such as ozone, nitrogen dioxide, carbon monoxide and dust particles etc. Low air quality can result in serious illnesses like cardiovascular disease and problems with respiration, as well as premature deaths