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