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http://dx.doi.org/10.9717/kmms.2015.18.4.524

A Novel Data Prediction Model using Data Weights and Neural Network based on R for Meaning Analysis between Data  

Jung, Se Hoon (Dept. of Multimedia Eng., Sunchon National University (Gwangyang SW Convergence Institute))
Kim, Jong Chan (Dept. of Computer Eng., Sunchon National University)
Sim, Chun Bo (Dept. of Multimedia Eng., Sunchon National University)
Publication Information
Journal of Korea Multimedia Society / v.18, no.4, 2015 , pp. 524-532 More about this Journal
Abstract
All data created in BigData times is included potentially meaning and correlation in data. A variety of data during a day in all society sectors has become created and stored. Research areas in analysis and grasp meaning between data is proceeding briskly. Especially, accuracy of meaning prediction and data imbalance problem between data for analysis is part in course of something important in data analysis field. In this paper, we proposed data prediction model based on data weights and neural network using R for meaning analysis between data. Proposed data prediction model is composed of classification model and analysis model. Classification model is working as weights application of normal distribution and optimum independent variable selection of multiple regression analysis. Analysis model role is increased prediction accuracy of output variable through neural network. Performance evaluation result, we were confirmed superiority of prediction model so that performance of result prediction through primitive data was measured 87.475% by proposed data prediction model.
Keywords
Data Analysis; Data Prediction; Data Weights; Artifical Neural Network; R;
Citations & Related Records
Times Cited By KSCI : 7  (Citation Analysis)
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