• Dhananjay P. Atole
• Prof. Rushi Longadge
• Prof. Deepak Kapgate

Abstract - India is an agricultural country so crop productivity is highly depends upon rainfall. For the better crop productivity rainfall prediction is necessary and required. There are several techniques of rainfall prediction. Data mining technique is used to calculate or analyze the rainfall prediction. In this paper focuses on several data mining techniques like empirical method and dynamic method which is essential to predict the rainfall. The empirical method predicts rainfall using regression, ANN, Fuzzy Logic and group method of data handling. The regression is Statistical empirical technique which is used for prediction. In this paper several methods are discussed, that explore which methods will be better for prediction of rainfall.

Keywords- Empirical method, Dynamic method, K-Nearest Neighbour algorithm, decision tree, neural network, MPR, MLR.

"A Review on Statistical Modeling for Rainfall prediction using Data mining Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.2, Issue 4, page no.937-939, April-2015, Available :http://www.jetir.org/papers/JETIR1504016.pdf

"A Review on Statistical Modeling for Rainfall prediction using Data mining Technique", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.2, Issue 4, page no. pp937-939, April-2015, Available at : http://www.jetir.org/papers/JETIR1504016.pdf