IRJET - Rainfall Forecasting using Weka Data Mining Tool

1. The document discusses using data mining tools like Naive Bayes, Decision Trees, K-Nearest Neighbors and Support Vector Machines to forecast rainfall using a dataset containing weather variables. 2. The algorithms were tested on a dataset containing 679 instances of weather data from Jaipur, India from 2016-2018. Naive Bayes achieved an accuracy of 80.56%, Decision Trees achieved 94.10% accuracy, KNN achieved 93.96% accuracy, and SVM achieved 93.66% accuracy. 3. The most accurate models for rainfall prediction based on this dataset and analysis were Decision Trees and K-Nearest Neighbors, which both achieved over 93% accuracy in their forecasts.