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Research Journal of Pharmacy and Technology
Year : 2017, Volume : 10, Issue : 7
First page : ( 2075) Last page : ( 2080)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2017.00362.6

Prediction of Student Academics Performance Based on their Previous Performance and Family Support

Kashyap Sonali*, Bajaj Shikhar, Hida Jabanjalin

School of Computing Science and Engineering, Vellore Institute of Technology Vellore, India

*Corresponding author e-mail: sonalikashyap11895@gmail.com

Online published on 17 October, 2017.

Abstract

Background and Objective

This project aims to analyze the addiction of student towards alcohol in early life and how that can affect their life. As it were Children who begin to drink by age 13 will probably go ahead to have more regrettable evaluations and most dire outcome imaginable, to be avoided from school. Materials and Methods: Our work intends to approach student addiction on alcohol in secondary level using Data Mining (DM) techniques. The concepts used are Classification and the algorithms of the data-mining and clustering to analyze the result. The outcome demonstrates that a decent prescient precision can be accomplished, given that dependence of liquor can affect to the understudy execution. Comes about: moreover, the outcome additionally gives the relationship between's liquor use and the social, sex and study time properties for every understudy.

Conclusion

On the combination of two or more Classification algorithms decision tree method is more effective in predicting the performance of the student. Orange tool is used for the report and analysis of the project.

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Keywords

Classification accuracy, Data Mining, Decision tree, Disease diagnosis, Prediction.

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