Dropout Classification through Discriminant Function Analysis: A Statistical Approach

Authors(2) :-Ajit Kumar Jain, C. K. Jha

Educational Data Mining is a promising area in which many researchers are working on various issues like performance evaluation, enrollment management, placement, and dropout. Dropout of the students from their courses is one of the serious problems that require more efforts by the researchers. By applying the statistical and data mining techniques in the student database, lots of useful information can be obtained that may be useful to find out the causes of the dropout. In addition to this, classification models can be designed that can predict whether the student is thinking about the dropout from the course. This prior knowledge about studentís view regarding the dropout can be used to find out the reasons for dropout as well as by providing the appropriate counseling to the student; dropout ratio can be marginally reduced. The objective of the proposed research is to design a classification model for the dropout using a statistical technique called Discriminant Function Analysis.

Authors and Affiliations

Ajit Kumar Jain
Department of Computer Science, Banasthali Vidyapith, Rajasthan, India
C. K. Jha
Professor, Department of Computer Science, Banasthali Vidyapith, Rajasthan, India

Discriminant Function Analysis, Educational Data Mining, Data Preprocessing, Cross-Validation.

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Publication Details

Published in : Volume 2 | Issue 4 | July-August 2017
Date of Publication : 2017-08-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 572-577
Manuscript Number : CSEIT1724142
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Ajit Kumar Jain, C. K. Jha, "Dropout Classification through Discriminant Function Analysis: A Statistical Approach ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 4, pp.572-577, July-August-2017.
Journal URL : http://ijsrcseit.com/CSEIT1724142

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