Abstract
Identification of fresh air by predicting air quality Index is very important for providing better healthy environment to the society. Air pollution causes a severe health issues for the humans as well as threat to the environment. Air quality is measured by predicting air quality Index using some parameters. Based on air quality index value range it’ll help to forecast the levels of human health concerns. This study proposes XGboost algorithm to forecast the air quality. When compared to other machine learning models, XGboost helps to predict the air quality with high accuracy rate.