Urban Air Quality Analysis and Prediction Using Machine Learning

Abstract

Air pollution is one of the influential factors that can affect the quality of every living being in the environment. Monitoring the air pollution is a scathing issue. In this work, air pollutant prediction is done using Machine learning techniques. K Means algorithm is used for clustering and different classifiers such as Multinominal Logistic Regression and Decision Tree algorithms are used to analyze the results based on available data in the R programming language. The results obtained using classifiers are compared based on error rate and accuracy. The multinominal logistic regression model has given high accuracy compared to decision tree model.