International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-9 Issue-1, November 2019 258 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: A4011119119/2019©BEIESP DOI: 10.35940/ijitee.A4011.119119 Abstract: Weather forecasting is essential because it helps to deal with the environment related future anomalies. Accurate and timely predications can contribute largely for taking safety measures in the ongoing projects such as agriculture tasks, flight operations, transportation tasks and many others. There are large number of meteorologist all over the world who are trying their level best to predict the aspects of environment using data mining techniques. This paper contains some of the best work done in rain fall prediction using data mining techniques. This paper helps the researchers to study the literature of this field in a crisp, summarized and encapsulated way. Keywords: Data mining, Bayesian Classifier, Clustering, Rain fall prediction, Linear Regression Technique, K-fold, Weather predictions, Multiple Regression Technique. I. INTRODUCTION Weather forecasting is essential because it helps in dealing with the environment related future anomalies. Accurate and timely predictions can contribute largely for taking safety measures in the ongoing projects such as agriculture tasks, flight operations, transportation tasks, and many others. There are a large number of meteorologist all over the world who are trying their level best to predict the aspects of the environment using data mining techniques. Rainfall is a complex atmospheric process and a result of interaction between several environmental aspects. It is a natural phenomenon yet very difficult to predict due to a large number of dependent factors such as temperature, relative humidity, wind speed, wind direction, cloud coverage. Rainfall involved a large number of atmospheric processes and almost all of them follow a complex nonlinear pattern. Rain is an essential part of the agriculture industry. In countries like India where 52.27% population directly or indirectly depends on agriculture for their living. By predicting rainfall accurately and precisely, we can take necessary measures to deal with the problems if they exist. Rainfall prediction is very important not only in the agriculture area but for the non-agriculture part. In some areas, landslides occur due to heavy rainfall which is capable Revised Manuscript Received on November 05, 2019. Deepak Sharma, Research Scholar, Department of computer science and applications, MD University, Rohtak, India. Email: erdeepaksharmabwn@gmail.com Dr. Priti Sharma, Assistant Professor, Department of computer science and applications, MD University, Rohtak, India. Email: pritish80@yahoo.co.in of huge damage to the living population. Rainfall prediction is an indispensable part of the flood management module. The season of heavy rain during the summer in hot Asian countries is called monsoon. A monsoon is a seasonal wind shift. Approximately 50% of India’s total food comes directly as a result of summer crops which can be delayed with the delay in monsoon. Also, low rainfall can cause a drought-like situation which India witnessed during the first two years of Sh. Narendra Modi govt. Approximately 70% annual rainfall witnessed during monsoon season in India. Farmers start planting crops with the arrival of monsoon rains in June. Whenever there is good monsoon season the output of farms goes high which increases demands of the consumer as well as the income of farmers. It also increases the buying capacity of the rural people which ultimately results in the economic growth of companies selling products in rural areas. However, a poor monsoon season decreases the income of farmers which leads to a decrease in the capacity to repay his loans which he had taken earlier for seeds and other requirements of cultivation. By Predicting rainfall, we can find out the details about the monsoon and can deal with the future problems with better arrangements. For example, if we are getting patterns of bad monsoon so in that case, we can arrange another method by which water can be supplied for the cultivation of crops. Fig. 1. Process of Data Mining Why rainfall predictions are not accurate? The answer to the question lies in the fact that rainfall is a nonlinear random natural phenomenon. It is practically not possible to tell that on which factors does rainfall actually depends and on which it doesn’ t. Rainfall also Rain Fall Prediction using Data Mining Techniques with Modernistic Schemes and Well-Formed Ideas Deepak Sharma, Priti Sharma DATA CLEANING DATA INTEGRATION NORMALIZATION DATA TRANSFORMATION PATTERN EVALUATION DATA PRESENTATION