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Predicting Students Grades Using Artificial Neural Networks and Support Vector Machine

Predicting Students Grades Using Artificial Neural Networks and Support Vector Machine
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Author(s): Sajid Umair (The University of Agriculture, Peshawar, Pakistan)and Muhammad Majid Sharif (National University of Sciences and Technology (NUST), Pakistan)
Copyright: 2019
Pages: 16
Source title: Advanced Methodologies and Technologies in Modern Education Delivery
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-7365-4.ch059

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Abstract

Prediction of student performance on the basis of habits has been a very important research topic in academics. Studies show that selection of the correct data set also plays a vital role in these predictions. In this chapter, the authors took data from different schools that contains student habits and their comments, analyzed it using latent semantic analysis to get semantics, and then used support vector machine to classify the data into two classes, important for prediction and not important. Finally, they used artificial neural networks to predict the grades of students. Regression was also used to predict data coming from support vector machine, while giving only the important data for prediction.

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