Open AccessDesign and Implementation of Rainfall Prediction Model using Supervised Machine Learning Data Mining Techniques
Author(s) -
Priti Sharma,
Deepak Sharma
Publication year - 2021
Publication title -
indian journal of data mining
Language(s) - English
Resource type - Journals
ISSN - 2582-9246
DOI - 10.54105/ijdm.b1615.111221
Subject(s) - data mining , artificial neural network , computer science , stock market prediction , field (mathematics) , outlier , data processing , predictive modelling , artificial intelligence , machine learning , stock market , database , mathematics , paleontology , horse , pure mathematics , biology
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.