PREDICTION OF STUDENTS' SUCCESS IN MATHEMATICS BY A CLASSIFICATION TECHNIQUE VIA POLYHEDRAL CONIC FUNCTIONS
Keywords:
Educational data mining, classification, polyhedral conic functions, mathematics educationAbstract
There has been a lot of work that has been already done using data mining in educational institutes and organizations and due to great success, the people are getting more and more interested in this field. In this paper a not long ago developped polyhedral conic functions classification algorithm is applied to a dataset of student performance in mathematics. Implemantations are made in MATLAB and WEKA. Results are shown in tables. This method can be applied to various datasets related with education. It will be helpfull for all educational fields.Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2016 The Eurasia Proceedings of Educational and Social Sciences
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The articles may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Authors alone are responsible for the contents of their articles. The journal owns the copyright of the articles. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of the research material. All authors are requested to disclose any actual or potential conflict of interest including any financial, personal or other relationships with other people or organizations regarding the submitted work.