Optimized Rainfall Prediction Model Using Optune CatBoost: An Innovative Approach

Rainfall forecasting is important for several uses, such as agriculture, water supply, and flooding emergencies. This is because rainfall, which is a type of precipitation, is not easily predictable owing to several factors that include atmospheric, oceanic, and geographical factors. Therefore, a new Optune CatBoost prediction model has been developed here that can be used to predict rainfall. Some of the research techniques used include; data preprocessing, outlier analysis, normalization, SMOTE, feature engineering, and correlation analysis. This Optune CatBoost prediction gives a maximum accuracy of 96% a precision of 97% F1 score of 96.7%, and recall of 95.5%. The discrimination between rainfall and non-RA events is evaluated to be strong with the area under the ROC curve equalling 0.96. The study implies that the developed model could be used to enhance rainfall prediction, which in turn aids in decision-making on appropriate resource utilization in weather-sensitive areas.