AIR QUALITY PREDICTION AND ANALYSIS USING MACHINE LEARNING

Abstract

The proposed system shows different models used for prediction of Air Quality Index (AQI) using various machine learning procedures. The system examines machine learning algorithm for air quality index by computing algorithm accuracy which will bring about the best precision. Moreover, the system shows various machine learning accuracy figures from the dataset values with assessment check report which recognize the proximity index. The results show the importance of ML suggested evaluation techniques which can be contrasted and best appropriateness with accuracy, realness and F1 Score. The air pollution datasets contain data for every state (zone) of India. Several machine learning algorithms like logistic regression, decision tree, support vector machine (SVM), random forest tree, Naïve Bayes theorem and K-nearest neighbor (KNN) are all parallels compared and evaluated.