Rainfall Prediction using Machine Learning Algorithms: A Comparative Analysis Approach

Rainfall prognosis is one of the most important technique to anticipate the climatic conditions across globe. Heavy Rainfall is a major issue for meteorological department as it is closely connected to the economy and life of human beings. It is a source for natural disasters like flood and drought which are encountered by people across the globe every year. Prompt and explicit predictions can assist proactively reduce human and financial loss. The paper introduces a Rainfall prediction model using Multi Linear Regression, Random Forest Regression and KNN Regression. The given input data is having numerous inputs and to anticipate the rainfall in more specific. The Mean Squared Error (MSE), accuracy score of training and testing, R2_Score for the parameters used to verify the proposed model. The comparative outcome among various algorithms is also presented in this paper