Educational Data Mining: RT and RF Classification Models for Higher Education Professional Courses
Автор: Siddu P. Algur, Prashant Bhat, Narasimha H Ayachit
Журнал: International Journal of Information Engineering and Electronic Business(IJIEEB) @ijieeb
Статья в выпуске: 2 vol.8, 2016 года.
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Computer applications and business administrations have gained significant importance in higher education. The type of education, students get in these areas depend on the geo-economical and the social demography. The choice of a institution in these area of higher education dependent on several factors like economic condition of students, geographical area of the institution, quality of educational organizations etc. To have a strategic approach for the development of importing knowledge in this area requires understanding the behavior aspect of these parameters. The scientific understanding of these can be had from obtaining patterns or recognizing the attribute behavior from previous academic years. Further, applying data mining tool to the previous data on the attributes identified will throw better light on the behavioral aspects of the identified patterns. In this paper, an attempt has been made to use of some techniques of education data mining on the dataset of MBA and MCA admission for the academic year 2014-15. The paper discusses the result obtained by applying RF and RT techniques. The results are analyzed for the knowledge discovery and are presented.
Data Mining, Educational Data Mining, Random Tree Classification, Random Forest Classification
Короткий адрес: https://sciup.org/15013411
IDR: 15013411
Список литературы Educational Data Mining: RT and RF Classification Models for Higher Education Professional Courses
- Ryan S.J.d. Baker, "Data Mining for Education". International Encyclopedia of Education (3rd edition). Oxford, UK: Elsevier 2010.
- Bhise R.B., Thorat S.S., and Supekar A.K, "Importance of Data Mining in Higher Education System", IOSR Journal Of Humanities And Social Science (IOSR-JHSS), Jan-Feb, 2013.
- Ogunde A. O and Ajibade D. A. ," A Data Mining System for Predicting University Students' Graduation Grades Using ID3 Decision Tree Algorithm ". Journal of Computer Science and Information Technology
- Sonali Agarwal, G. N. Pandey, and M. D. Tiwari, "Data Mining in Education: Data Classification and Decision Tree Approach", International Journal of e-Education, e-Business, e-Management and e-Learning, Vol. 2, No. 2, April 2012.
- Brijesh Kumar Baradwaj and Saurabh Pal, "Mining Educational Data to Analyze Students Performance", International Journal of Advanced Computer Science and Applications, 2011.
- Jing Luan, "Data Mining Applications in Higher Eduacation", SPSS publications.
- Sunita B Aher and Lobo, "Data Mining in Educational System using WEKA", International Conference on Emerging Technology Trends (ICETT) 2011.
- Monika Goyal and Rajan Vohra, "Applications of Data Mining in Higher Education", International Journal of Computer Science Issues, Vol. 9, Issue 2, No 1, March 2012.
- M. Durairaj, C. Vijitha, "Educational Data mining for Prediction of Student Performance Using Clustering Algorithms", International Journal of Computer Science and Information Technologies, Vol. 5 (4) , 2014, 5987-5991
- Naeimeh DELAVARI, Somnuk PHON-AMNUAISUK, Mohammad Reza BEIKZADEH, "Data Mining Application in Higher Learning Institutions", Informatics in Education, 2008, Vol. 7, No. 1, 31–54
- Romero, C.Ventura, S. and Garcia, "Data mining in course management systems: Model case study and Tutorial". Computers & Education,Vol. 51, No. 1. pp.368- 384. 2008.
- Samrat Singh and Dr. Vikesh Kumar, "Performance analysis of Engineering Students for Recruitment Using Classification Techniques", IJCSET February 2013 Vol 3, Issue 2, 31-37.
- Romero,C. and Ventura, S. ,"Educational data Mining: A Survey from 1995 to 2005".Expert Systems with Applications (33) 135-146. 2007.
- Jai Ruby and Dr. K. David, "Analysis of Influencing Factors in Predicting Students Performance Using MLP –AComparative Study", 10.15680/ijircce.2015.0302070.
- Ritika Saxena, "Educational data Mining: Performance Evaluation of Decision Tree and Clustering Techniques using WEKA Platform", International Journal of Computer Science and Business Informatics, MARCH 2015.
- M.I. López, J.M Luna, C. Romero and S. Ventura, "Classification via clustering for predicting final marks based on student participation in forums" Regional Government of Andalusia and the Spanish Ministry of Science and Technology projects.
- Sunita B Aher and Mr. LOBO L.M.R.J, "Data Mining in Educational System using WEKA", International Conference on Emerging Technology Trends (ICETT) 2011.
- Siddu p. Algur and Prashant Bhat, "Metadata Based Classification and Analysis of Large Scale Web Videos", Interanational Journal of Emerging Trends and Technologies, May-June, 2015.
- Srecko Natek and Moti Zwilling, "Data Mining For Small Student Data Set – Knowledge Management System For Higher Education Teachers", Knowledge Management and Innovation, International Conference, 2013.
- Dorina Kabakchieva, "Predicting Student Performance by Using Data Mining Methods for Classification", Cybernetics And Information Technologies, Volume 13, No 1, 2013.
