Estimation of Rainfall Quantity using Hybrid Ensemble Regression

Accurate prediction of rainfall in a geographical region has always been a challenge to the researchers. In this paper, ensemble methods such as bagging and boosting are used to predict rainfall level in districts belonging to Tamil Nadu, India. The Ensemble Regression models are optimised by tuning the parameters such as the number of estimators, base estimator and maximum depth. For evaluating the developed models, performance measures such as Mean Squared Error and Explained Variance Score were used. Based on the analysis, Bagging Regression produced better results than the other models after optimisation, but the difference between the performance of the models was very less. Hence, the prediction of the ensemble regression models is used instead of the features to predict rainfall, where two or more models are used at a time in different combinations for this purpose. The models are combined in different combinations using ensemble techniques such as Simple Averaging, Blending and Stacking. The developed models are compared using graphical analysis, where the comparison is based on actual rainfall values.