Manuscript Rainfall Prediction using Support Vector Machine (SVM)

In the course of this research, we conducted an examination that specifically aimed to predict hourly rainfall. The approach we adopted for this analysis treated the problem as a binary classification task, where we categorized rainfall events into two groups: “rainy” (considered the positive class) and “non-rainy” (designated as the negative class). To forecast rainfall conditions for the upcoming hour, we utilized various independent climatic variables from the current hour. The data source we utilized was the CST weather station, which provided us with records of eight hourly weather parameters. To make our predictions, we employed a widely used machine learning model known as the Support Vector Machine(SVM), and this yielded an accuracy rate of 78%.