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Selecting the Best Supervised Learning Algorithm for Recommending the Course in E-Learning System

by Sunita B Aher, Lobo L.m.r.j.
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 5
Year of Publication: 2012
Authors: Sunita B Aher, Lobo L.m.r.j.
10.5120/5541-7597

Sunita B Aher, Lobo L.m.r.j. . Selecting the Best Supervised Learning Algorithm for Recommending the Course in E-Learning System. International Journal of Computer Applications. 41, 5 ( March 2012), 42-49. DOI=10.5120/5541-7597

@article{ 10.5120/5541-7597,
author = { Sunita B Aher, Lobo L.m.r.j. },
title = { Selecting the Best Supervised Learning Algorithm for Recommending the Course in E-Learning System },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 5 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 42-49 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number5/5541-7597/ },
doi = { 10.5120/5541-7597 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:28:52.157583+05:30
%A Sunita B Aher
%A Lobo L.m.r.j.
%T Selecting the Best Supervised Learning Algorithm for Recommending the Course in E-Learning System
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 5
%P 42-49
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Now a day E-learning is becoming popular as it helps to fulfil the necessities of remote students and helps the teaching-learning process in Education system. Course Recommender System in E-Learning is a system which recommend the course to the student based on the choice of various student collected from huge amount of data of courses offered through Moodle package of the college. Here in this paper we compare the seven classification algorithm to choose the best classification algorithm for Course Recommendation system. Theses seven classification algorithms are ADTree, Simple Cart, J48, ZeroR, Naive Bays, Decision Table & Random Forest Classification Algorithm. We compare these seven algorithms using open source data mining tool Weka & present the result. We found that ADTree classification algorithm works better for this Course Recommender System than other five classification algorithms.

References
  1. Hu H. , Li J. , Plank A. , Wang H. and Daggard G. , "A Comparative Study of Classification Methods for Microarray Data Analysis", In Proc. Fifth Australasian Data Mining Conference, Sydney, Australia (2006).
  2. Abdelghani Bellaachia, Erhan Guven, "Predicting Breast Cancer Survivability Using Data Mining Techniques" accessed from http://www. siam. org/meetings/sdm06/workproceed/Scientific%20Datasets/bellaachia. pdf on 05-03-2012
  3. My Chau Tu, Dongil Shin, Dongkyoo Shin, "A Comparative Study of Medical Data Classification Methods Based on Decision Tree and Bagging Algorithms", dasc, pp. 183-187, 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing, 2009.
  4. Aman Kumar Sharma, Suruchi Sahni:"A Comparative Study of Classification Algorithms for Spam Email Data Analysis" in International Journal on Computer Science and Engineering (IJCSE)
  5. Rich Caruana Alexandru Niculescu-Mizil," An Empirical Comparison of Supervised Learning Algorithms" ICML '06 Proceedings of the 23rd international conference on Machine learning. ISBN:1-59593-383-2 doi>10. 1145/1143844. 1143865
  6. ERIC BAUER, RON KOHAVI," An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants" Machine Learning, vv, 1{38 (1998) Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
  7. TJEN-SIEN LIM, WEI-YIN LOH, YU-SHAN SHIH," A Comparison of Prediction Accuracy, Complexity, and Training Time of Thirty-three Old and New Classi_cation Algorithms" Machine Learning, 40, 203{229 (2000) Kluwer Academic Publishers, Boston. Manufactured in The Netherlands.
  8. Weka (2007). http://www. cs. waikato. ac. nz/ml/weka/.
  9. "Data Mining Introductory and Advanced Topics" by Margaret H. Dunham
  10. Sunita B Aher and Lobo L. M. R. J. . Data Mining in Educational System using WEKA. IJCA Proceedings on International Conference on Emerging Technology Trends (ICETT) (3):20-25, 2011. Published by Foundation of Computer Science, New York, USA (ISBN: 978-93-80864-71-13)
  11. Sunita B Aher and Lobo L. M. R. J. Article: A Framework for Recommendation of courses in E-learning System. International Journal of Computer Applications 35(4):21-28, December 2011. Published by Foundation of Computer Science, New York, USA ISSN 0975 – 8887 Digital Library URI: http://www. ijcaonline. org/archives/volume35/number4/4389-6091.
  12. http://www. d. umn. edu/~padhy005/Chapter5. html accessed on 30-01-2012
  13. http://en. wikipedia. org/wiki/Random_forest accessed on 30-01-2012
  14. Sunita B Aher and Lobo L. M. R. J. Article: Mining Association Rule in Classified Data for Course Recommender System in E-Learning. International Journal of Computer Applications 39(7):1-7, February 2012. Published by Foundation of Computer Science, New York, USA. ISSN 0975 – 8887 Digital Library URI: http://www. ijcaonline. org/archives/volume39/number7/4829-7086
  15. Sunita B Aher and Lobo L. M. R. J. ,"Data Preparation Strategy in E-Learning System using Association Rule Algorithm" selected in International Journal of Computer Applications. Published by Foundation of Computer Science, New York, USA. ISSN 0975 – 8887
  16. http://en. wikipedia. org/wiki/Alternating_decision_tree accessed on dat 02-02-2012
Index Terms

Computer Science
Information Sciences

Keywords

Adtree Simple Cart J48 Zeror Naive Bays Decision Table Random Forest Classification Algorithm Weka

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