CFP last date
20 March 2024
Reseach Article

Comparative Analysis of Various Data Mining Techniques on Educational Datasets

by Sumit Garg, Arvind K. Sharma
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 74 - Number 5
Year of Publication: 2013
Authors: Sumit Garg, Arvind K. Sharma
10.5120/12878-9673

Sumit Garg, Arvind K. Sharma . Comparative Analysis of Various Data Mining Techniques on Educational Datasets. International Journal of Computer Applications. 74, 5 ( July 2013), 1-5. DOI=10.5120/12878-9673

@article{ 10.5120/12878-9673,
author = { Sumit Garg, Arvind K. Sharma },
title = { Comparative Analysis of Various Data Mining Techniques on Educational Datasets },
journal = { International Journal of Computer Applications },
issue_date = { July 2013 },
volume = { 74 },
number = { 5 },
month = { July },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume74/number5/12878-9673/ },
doi = { 10.5120/12878-9673 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:41:23.329291+05:30
%A Sumit Garg
%A Arvind K. Sharma
%T Comparative Analysis of Various Data Mining Techniques on Educational Datasets
%J International Journal of Computer Applications
%@ 0975-8887
%V 74
%N 5
%P 1-5
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining is a relatively young and interdisciplinary field of computer science. It is a process that attempts to discover new patterns in large data sets. Different types of mining algorithms have been proposed by different researchers in recent years. A single algorithm may not be applied to all applications due to difficulty for suitable data types of the algorithm. Therefore the selection of a correct data mining algorithm depends on not only the goal of an application, but also on the compatibility of the data set. The aim of this paper is how to use suitable data mining algorithms on educational dataset. This paper focuses on comparative analysis of various data mining techniques and algorithms.

References
  1. Bharati M. Ramageri, "Data Mining Techniques and Application", Indian Journal of Computer Science and Engineering, Vol. 1 No. 4; pp. 301-305.
  2. Velmurugan T. et al. , "Performance Evaluation of K-Means & fuzzy C-means Clustering Algorithm for Statistical Distribution of Input Data Points", European Journal of Scientific Research, Vol. 46, 2010.
  3. Kavitha P. , T. Sasipraba, "Performance Evaluation of Algorithms using a Distributed Data Mining Framework based on Association Rule Mining", International Journal on Computer Science & Engineering (IJCSE), 2011.
  4. Yujie Zheng, "Clustering Methods in Data Mining with its Application in Higher Education", International Conference on Education Technology and Computer, Vol. 43, 2012, IACSIT Press, Singapore.
  5. M. Sukan et al. , "Data Mining: Performance Improvement in Education Sector using Classification and Clustering Algorithm", International Conference of Computing and Control Engineering (ICCCE) 12-13 April, 2012.
  6. Manoj Bala et al. , "Study of Application of Data Mining Technique in Education", International Journal of Research in Science and Technology, Vol. No. 1, Issue No. IV, Jan-March, 2012.
  7. Hamidah Jantan, "Classification and Prediction of Academic Talent using Data Mining Technique", 14 International Conference on Knowledge based and Intelligent Information and Engineering Information pages 491-500.
  8. Tai Chang Hsia, "Course Planning of Extension Education to meet Market Demand by using Data Mining Techniques", Expert System with Applications: An International Journal, Vol. 34, Issue-1, Jan 2008.
  9. Jiawei Han and Michelire Kamber, "Data Mining Concept and Technique", Published by Morgan Kaufman, 2006.
  10. Monika Goyal and Rajan Vohra, "Application of Data Mining in Higher Education", International Journal of Computer Science(IJCSI) Issues, Vol. 9, Issue-2, No. 1, March 2012; pp-113-120.
  11. Arun K Pujari, "Data mining Technique", Published by Universities Press (I) Pvt. Ltd, Hyderabad, India.
  12. Gajendra Sharma, "Data mining and Data Warehousing and OLAP", Published by S. K. Kataria & Sons, New Delhi, India.
  13. Arvind Sharma et al. , "Data Mining Techniques and Their Implementation in Blood Bank Sector-A Review", International Journal of Engineering Research and Application (IJERA), Vol. 2, Issue-4, July-August 2012; pp. 1303-1309.
  14. R. K. Somani, "Data Mining & Warehousing", College Book Centre, Chaura Rasta, Jaipur, India.
  15. Venkatadri. M, "A Review on Data Mining from Past to Future", International Journal of Computer Applications (IJCA), Vol. 15, No. 7, Feb 2011.
  16. http://www. cs. waikato. ac. nz/~ml/weka/
Index Terms

Computer Science
Information Sciences

Keywords

Data Mining Techniques Educational Dataset WEKA