Classification of Rainfall Levels using Various Machine Learning Techniques

The estimation of rainfall level in advance is a very challenging task due to major deviations in the climatic conditions of India. So, there is a need to develop some mechanism to solve this classification problem with the highest accuracy. It gives a direction to proceed with this research work. In this work, the binary classification of rainfall values is carried out for the provided input parameters i. e. Maximum temperature and Humidity. For, this various machine learning based classification models, such as Gaussian Naive Bayes, Kernel Naive Bayes, Fine KNN, Cubic KNN, Fine tree, and Coarse tree, have been developed using the MATLAB (R2021a). Each model is designed using the K-point cross validation approach. The confusion matrices of all the models are analyzed and their accuracies are compared.