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Classifying Student’s Learning Experience using Improved Apriori and CART
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 174 - Number 1 |
| Year of Publication: 2017 |
| Authors: Pooja Verma, Rajesh Boghey, Sandeep Rai |
10.5120/ijca2017915311
|
Pooja Verma, Rajesh Boghey, Sandeep Rai . Classifying Student’s Learning Experience using Improved Apriori and CART. International Journal of Computer Applications. 174, 1 ( Sep 2017), 34-40. DOI=10.5120/ijca2017915311
Abstract
Here in this paper a new of classifying Student’s learning experience on online social networks such as facebook, twitter is proposed which helps to find various issues and problems in their educational experiences. The existing technique implemented for the classification for the Student's learning experience provides multi-label classification to reflect various problems but fails to provide the improvement in accuracy, hence a new multi-label classification using improved Apriori algorithm is proposed which generates a set of candidate rules and finally classify Student's experience using Classification & Regression Tree. The proposed methodology implemented provides better results in comparison with an existing technique. The experimental results are performed and tested on various parameters such as precision and recall and final Score. The various student's learning experience and their classification is done here using Fuzzy-Apriori and CART provide and better way to final and issue problems in various fields.
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