Research Article
ID3 Classifier for Pupils’ Status Prediction
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 57 - Issue 3 |
| Published: November 2012 |
| Authors: K. Nandhini, S. Saranya |
10.5120/9094-3133
|
K. Nandhini, S. Saranya . ID3 Classifier for Pupils’ Status Prediction. International Journal of Computer Applications. 57, 3 (November 2012), 14-18. DOI=10.5120/9094-3133
@article{ 10.5120/9094-3133,
author = { K. Nandhini,S. Saranya },
title = { ID3 Classifier for Pupils’ Status Prediction },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 57 },
number = { 3 },
pages = { 14-18 },
doi = { 10.5120/9094-3133 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A K. Nandhini
%A S. Saranya
%T ID3 Classifier for Pupils’ Status Prediction%T
%J International Journal of Computer Applications
%V 57
%N 3
%P 14-18
%R 10.5120/9094-3133
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Predicting the pupil's status is the primary goal. Many studies have been made by a large number of scientists to explore the prediction of their research. One best solution is predicting the results based on the data source by applying some data mining techniques. This research work is to identify the prediction results by means of applying classification technique on the data source being available. There are many approaches in classification technique but this paper implements ID3 (Iterative Dichotomiser 3) Decision Tree concept which provides higher accuracy rates. This model extracts highly useful, reliable patterns from the database to ensure pupil's to achieve a higher academic output.
References
- Andrew Colin, "Building Decision Trees with the ID3 Algorithm", by: Dr. Dobbs Journal, June 1996.
- Galit. et. al, "Examining online learning processes based on log files analysis: a case study". Research, Reflection and Innovations in Integrating ICT in Education 2007.
- J. Han and M. Kamber, "Data Mining: Concepts and Techniques," Morgan Kaufmann, 2000.
- M. Bray, The Shadow Education System: Private Tutoring and Its Implications for Planners, (2nd ed. ), UNESCO, PARIS, FRANCE, 2007.
- P. Cortez, and A. Silva, "Using Data Mining To Predict Secondary School Student Performance", In EUROSIS, A. Brito and J. Teixeira (Eds. ), 2008, pp. 5-12.
- Q. A. AI-Radaideh, E. W. AI-Shawakfa, and M. I. AI-Najjar, "Mining student data using decision trees", International Arab Conference on Information Technology(ACIT'2006), Yarmouk University, Jordan, 2006.
- S. T. Hijazi, and R. S. M. M. Naqvi, "Factors Affecting Student's Performance: A Case of Private Colleges", Bangladesh e-Journal of Sociology, Vol. 3, No. 1, 2006.
- U. K. Pandey, and S. Pal, "A Data mining view on class room teaching language", (IJCSI) International Journal of Computer Science Issue, Vol. 8, Issue 2, pp. 277-282, ISSN:1694-0814, 2011.
- Z. N. Khan, "Scholastic Achievement of Higher Secondary Students in Science Stream", Journal of Social Sciences, Vol. 1, No. 2, 2005, pp. 84-87.
Index Terms
Keywords