International Journal of Information Engineering and Electronic Business (IJIEEB)
IJIEEB Vol. 8, No. 2, 8 Mar. 2016
Cover page and Table of Contents: PDF (size: 464KB)
Educational Data Mining: RT and RF Classification Models for Higher Education Professional Courses
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Author(s)
Index Terms
Data Mining, Educational Data Mining, Random Tree Classification, Random Forest Classification
Abstract
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.
Cite This Paper
Siddu P. Algur, Prashant Bhat, Narasimha H Ayachit, "Educational Data Mining: RT and RF Classification Models for Higher Education Professional Courses", International Journal of Information Engineering and Electronic Business(IJIEEB), Vol.8, No.2, pp.59-65, 2016. DOI:10.5815/ijieeb.2016.02.07
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