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Application of k Means Clustering algorithm for prediction of Students Academic Performance

Domaine:

education

Type de record:

paper
Créateur:
OyeOlaOba
Éditeur:
arXiv
Hôte:avatar
The ability to monitor the progress of students academic performance is a critical issue to the academic community of higher learning. A system for analyzing students results based on cluster analysis and uses standard statistical algorithms to arrange their scores data according to the level of their performance is described. In this paper, we also implemented k mean clustering algorithm for analyzing students result data. The model was combined with the deterministic model to analyze the students results of a private Institution in Nigeria which is a good benchmark to monitor the progression of academic performance of students in higher Institution for the purpose of making an effective decision by the academic planners. IEEE format, International Journal of Computer Science and Information Security, IJCSIS January 2010, ISSN 1947 5500, sites.google.com

Visit

doi.orgarxiv.org

Tags

Machine Learning (cs.LG)Computers and Society (cs.CY)FOS: Computer and information sciencesFOS: Computer and information sciences

Licenses

arXiv.org perpetual, non-exclusive licensehttp://arxiv.org/licenses/nonexclusive-distrib/1.0/

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