An Empirical Study of Rainfall Prediction Using Various Regression Models

Rainfall forecasting is difficult since the weather always delays its parameters for less than a minute. Depending on one’s abilities at work, accurate predictions can aid a person and lessen asset loss. This article provides a series of experiments that employ popular machine-learning techniques to create models that forecast whether or not it will rain tomorrow based on weather information from the previous day. This comparative study emphasizes on three aspects that are Data collection, pre-processing methods, and data modelling. The findings compare multiple measures for evaluating machine learning approaches and their accuracy in predicting rainfall by examining weather data. Additionally, it uses data provided by the user to predict rainfall using the most accurate algorithm.