Academic performance prediction based on voting technique

Muhammad Sufyian Mohd Azmi, Ikmal Hisyam Bin Mohamad Paris

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Student's grade has always been critical issues that occur quite often in universities providing high learning education. Currently there are many techniques to predict student's grade. In this paper we compare the accuracy of data mining methods to classifying students in order to predicting student's class grade. These predictions are more useful for identifying weak students and assisting management to take remedial measures at early stages to produce excellent graduate that will graduate at least with second class upper. Firstly we examine single classifiers accuracy on our data set and choose the best one and then ensembles it with a weak classifier to produce simple voting method. We present results show that combining different classifiers outperformed other single classifiers for predicting student performance.

Original languageEnglish
Title of host publication2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011
Pages24-27
Number of pages4
DOIs
Publication statusPublished - 29 Sep 2011
Event2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011 - Xi'an, China
Duration: 27 May 201129 May 2011

Publication series

Name2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011

Other

Other2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011
CountryChina
CityXi'an
Period27/05/1129/05/11

Fingerprint

Students
Classifiers
Data mining
Education

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Software

Cite this

Mohd Azmi, M. S., & Paris, I. H. B. M. (2011). Academic performance prediction based on voting technique. In 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011 (pp. 24-27). [6014841] (2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011). https://doi.org/10.1109/ICCSN.2011.6014841
Mohd Azmi, Muhammad Sufyian ; Paris, Ikmal Hisyam Bin Mohamad. / Academic performance prediction based on voting technique. 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011. 2011. pp. 24-27 (2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011).
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abstract = "Student's grade has always been critical issues that occur quite often in universities providing high learning education. Currently there are many techniques to predict student's grade. In this paper we compare the accuracy of data mining methods to classifying students in order to predicting student's class grade. These predictions are more useful for identifying weak students and assisting management to take remedial measures at early stages to produce excellent graduate that will graduate at least with second class upper. Firstly we examine single classifiers accuracy on our data set and choose the best one and then ensembles it with a weak classifier to produce simple voting method. We present results show that combining different classifiers outperformed other single classifiers for predicting student performance.",
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Mohd Azmi, MS & Paris, IHBM 2011, Academic performance prediction based on voting technique. in 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011., 6014841, 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011, pp. 24-27, 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011, Xi'an, China, 27/05/11. https://doi.org/10.1109/ICCSN.2011.6014841

Academic performance prediction based on voting technique. / Mohd Azmi, Muhammad Sufyian; Paris, Ikmal Hisyam Bin Mohamad.

2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011. 2011. p. 24-27 6014841 (2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Academic performance prediction based on voting technique

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N2 - Student's grade has always been critical issues that occur quite often in universities providing high learning education. Currently there are many techniques to predict student's grade. In this paper we compare the accuracy of data mining methods to classifying students in order to predicting student's class grade. These predictions are more useful for identifying weak students and assisting management to take remedial measures at early stages to produce excellent graduate that will graduate at least with second class upper. Firstly we examine single classifiers accuracy on our data set and choose the best one and then ensembles it with a weak classifier to produce simple voting method. We present results show that combining different classifiers outperformed other single classifiers for predicting student performance.

AB - Student's grade has always been critical issues that occur quite often in universities providing high learning education. Currently there are many techniques to predict student's grade. In this paper we compare the accuracy of data mining methods to classifying students in order to predicting student's class grade. These predictions are more useful for identifying weak students and assisting management to take remedial measures at early stages to produce excellent graduate that will graduate at least with second class upper. Firstly we examine single classifiers accuracy on our data set and choose the best one and then ensembles it with a weak classifier to produce simple voting method. We present results show that combining different classifiers outperformed other single classifiers for predicting student performance.

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Mohd Azmi MS, Paris IHBM. Academic performance prediction based on voting technique. In 2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011. 2011. p. 24-27. 6014841. (2011 IEEE 3rd International Conference on Communication Software and Networks, ICCSN 2011). https://doi.org/10.1109/ICCSN.2011.6014841