Machine Learning Approaches Used for Air Quality Forecast: A Review

Air Quality Index (AQI) is an indicator of the pollution level our surroundings and household. Prediction AQI values from historical can help us analyze mitigate levels. The be classified into predetermined categories machine learning algorithms made use to improve classification accuracy value calculated. main objective paper provide potential researchers, with importance various Machine Learning approaches used for forecast Index. This analyzes strategies prediction, incorporating techniques. air quality index calculated using learning-based methods. Some methods considered are logistic regression, decision tree, support vector classifier, random forest Naive Bayes K-nearest neighbor. Application these on datasets may yield different Accuracy, Recall, F1 Score. Different that said purpose their strengths summarized in a comparison table.