PREDICTION & WARNING

Author:

Arora Yojna1,Singhal Abhishek1,Bansal Abhay1

Affiliation:

1. Amity University, Noida, Uttar Pradesh, India

Abstract

Educational data mining is a new discipline, which aims at extracting useful information and thus knowledge from huge data sets present at Educational Institutions. The main aim for such a discipline is to improve the quality of education by analyzing every parameter that is related to it. This is a Non-Linear Problem. Machine Learning provides various algorithms and approaches to deal with problems related to determining education quality. For the present study, a prediction model based on the Radial Basis Function (RBF) is proposed and its aim is to predict marks obtained by students in a subject that is related to subjects taken during previous semesters. Based on the results of predicted performance thus obtained, students are categorized into groups and the students likely to fail are warned beforehand for improvement.

Publisher

Association for Computing Machinery (ACM)

Reference13 articles.

1. Lin-Tao Lv Na Ji and Jhu- Long Zhang.2009. A RBF Neural Network Model For Anti-Money Laundering In Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition Hong Kong 30--31 Lin-Tao Lv Na Ji and Jhu- Long Zhang.2009. A RBF Neural Network Model For Anti-Money Laundering In Proceedings of the 2008 International Conference on Wavelet Analysis and Pattern Recognition Hong Kong 30--31

2. Lean Yu Kin Keung Lai and Shouyang Wang.2008. Multistage RBF neural network ensemble learning for exchange rates forecasting.Neurocomputing 10.1016/j.neucom.2008.04.029 Lean Yu Kin Keung Lai and Shouyang Wang.2008. Multistage RBF neural network ensemble learning for exchange rates forecasting.Neurocomputing 10.1016/j.neucom.2008.04.029

3. An Efficient Weather Forecasting System using Radial Basis Function Neural Network

4. Ryan S.J.D. Baker Kalina Yacef. The State of Educational Data Mining in 2009: A Review and Future Visions. Ryan S.J.D. Baker Kalina Yacef. The State of Educational Data Mining in 2009: A Review and Future Visions.

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