Utilizing Machine Learning Algorithms for Rainfall Analysis

Agriculture relies greatly on rainfall. Recent years witnessed a substantial improvement in the complexity of rainfall prediction. Rainfall forecast will provide valuable predictions to farmers to help them take the appropriate precautions to protect their crops from various weather conditions. Several techniques are available to predict rainfall. Machine Learning (ML) algorithms are particularly useful for predicting rainfall. As machine learning is a type of Artificial Intelligence (AI), it is essential for anticipating rainfall as it enables computer algorithms to make predictions more correctly without explicit guidance. Machine Learning (ML) uses previous data as input to predict the new output values. Meteorologists have attempted to predict future rainfall patterns via previous data. This method is referred to as rainfall forecasting. The primary objective of this research is to identify the best algorithm for predicting rainfall. In this work, SVR (Support Vector Regression) and linear regression strategies were used.