Design and Implementation of Rainfall Prediction Model using Supervised Machine Learning Data Mining Techniques

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Deepak Sharma
Dr. Priti Sharma

Abstract

Data mining is a rapidly developing technology that has enriched a lot of field such as business analysis, market analysis, weather forecasting, stock market analysis and many more. It starts with collecting data sets from reliable sources and pre-processing that data. There are some anomalies associated with data collected in large volumes such as outliers, missing values, and duplicated values. Remove these kinds of anomalies is teamed as pre-processing of data. In this paper, collection of weather data and pre-processing it for rainfall prediction model using Rapid Miner tool has been discussed. Also, artificial neural network data mining techniques is used to design a rainfall prediction model. ANN classification techniques is a complex data mining technique results in high accuracy in prediction of rainfall.

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[1]
Deepak Sharma and Dr. Priti Sharma , Trans., “Design and Implementation of Rainfall Prediction Model using Supervised Machine Learning Data Mining Techniques”, IJDM, vol. 1, no. 2, pp. 20–26, Jan. 2024, doi: 10.54105/ijdm.B1615.111221.
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How to Cite

[1]
Deepak Sharma and Dr. Priti Sharma , Trans., “Design and Implementation of Rainfall Prediction Model using Supervised Machine Learning Data Mining Techniques”, IJDM, vol. 1, no. 2, pp. 20–26, Jan. 2024, doi: 10.54105/ijdm.B1615.111221.
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