A Survey on Clustering and Feature Selection Algorithm for Quickly Predicting Engineering Students' Academic Performance

Authors

  • Susheelamma K H  Assistant Professor Department of ISE SJCIT, Chickballapur, Karnataka, India
  • Dr. Brahmananda S H   Professor and Head Department of CSE GITAM School of Technology Bengaluru, Karnataka, India

Keywords:

DM, EDM, CFOA, Clustering, Feature Selection.

Abstract

Data mining(DM) is the process of extracting hidden and useful information in large data repositories. Knowledge Discovery in large data repositories is time consuming hence the need for fast algorithms for extracting useful knowledge from large database. This knowledge can be used to increase the quality of education. Educational Data Mining(EDM) is concerned with developing new methods to discover knowledge from educational/academic database and can be used for decision making in educational/academic systems. In our survey paper we would like to focus and analyze the various Data clustering and feature selection algorithms to bring the clarity in students’ results and faculties contribution to make this one as success.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2018-02-28

Issue

Volume 4, Issue 1, January-February-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Susheelamma K H, Dr. Brahmananda S H , " A Survey on Clustering and Feature Selection Algorithm for Quickly Predicting Engineering Students' Academic Performance, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 1, pp.1486-1489, January-February-2018.