Association Rule Mining and Classifier Approach for Quantitative Spot Rainfall Prediction

Rainfall prediction is usually done for a region but spot quantitative precipitation forecast is required for individual township, harbours and stations with vital installation. A methodology using data mining technique has been tried for a coastal station, Cuddalore in East Coast of India and the results are presented here. The method gives good result for the prediction of daily rainfall 24 hours ahead. There are three main parts in this work. First, the obtained raw data was filtered using discretization approach based on the best fit ranges. Then, association mining has been performed on dataset using Predictive Apriori algorithm. Thirdly, the data has been validated using K classifier approach. Results show that the overall classification accuracy of the data mining technique is satisfactory.