Rainfall Forecasting using Machine Learning Techniques

Rainfall prophesies essentially resolves in the scientific research fields of both meteorological and hydrological environment. Rainfall prediction is very much important for
analyzing crop production, usage of water resources as well as pre-planning resources. Nevertheless, numerical forecasting techniques outcomes generate low prediction exactness for rainfall forecasting at most of the times. In this research, Machine learning methods ignore the
effects of physical variables in upstream or other downstream regions, allowing predictive accuracy to fluctuate in different areas. Moreover, Machine Learning techniques namely linear regression, Support vector machine are primarily used to enhance the overall forecasting accuracy for the rainfall through statistical analysis using data mining approach. Along with that, this paper introduces detection accuracy used by various scientists for evaluating the overall performance by calculating metrics such as accuracy, recall, r2-score.