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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 6, 2021.
Abstract: e-Learning is appropriate when the learners are grouped and facilitated to learn according to their learning style and at their own pace. Elaborate researches have been proposed to categorize learners based on various e-learning parameters. Most of these researches have deployed the clustering principles for grouping eLearners, and in particular, they have utilized K-Medoid principle for better clustering. In the classical K-Medoid algorithm, predicting or determining the value of K is critical, two methods namely the Elbow and Silhouette methods are widely applied. In this paper, we experiment with the application of both these methods to determine the value of K for clustering eLearners in K-Medoid and prove that Silhouette method best predicts the value of K.
S. Anthony Philomen Raj and Vidyaathulasiraman, “Determining Optimal Number of K for e-Learning Groups Clustered using K-Medoid” International Journal of Advanced Computer Science and Applications(IJACSA), 12(6), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120644
@article{Raj2021,
title = {Determining Optimal Number of K for e-Learning Groups Clustered using K-Medoid},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120644},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120644},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {6},
author = {S. Anthony Philomen Raj and Vidyaathulasiraman}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.