Prediction of Air Pollution using Supervised Machine Learning

The prediction and estimation of the air pollution stands a necessary analysis area. The main abstract of this is to explore machine learning which is used for checking of air quality forecasting to predict the outcome in best accuracy. In supervised machine learning this analysis is done to measure information like identification of variable and analysis of univariate, bivariate and multivariate analysis and identify the values which are missed and used to analyze validation of data and cleaning of data and visualization of data is done by entire by dataset. This analysis is to provide complete guide to sensitive analysis of parameters in addition to forecasting of air pollution by accurate prediction. This analysis is to suggest framework to expect the index of air excellence by predicting the results to form good accuracy and used to compare supervise classification machine learning algorithms. In addition it is to discuss the algorithm from the dataset taken from traffic department with graphic user interface air quality prediction.