STAT-X: short-term atmospheric temperature forecasting using machine learning models with explainable-AI
摘要
This research explores the use of supervised machine learning algorithms to predict the minimum and maximum temperatures for the next three days in a locality, more precisely in a city using a time-series dataset. Here we have assessed it with 13 weather features spanning 1973–2024 in Kolkata, India. The study used six well-known algorithms— linear regression, decision tree regressor, random forest regressor, bagging regressor, and gradient boosting regressor, finding that the gradient boosting regressor, followed by the multi-layer perceptron, performs the best. Using the past 10 days’ data, these models provided accurate predictions, validated by low error, high