Medoid-based shadow value validation and visualization

A silhouette index is a well-known measure of an internal criteria validation for the clustering algorithm results. While it is a medoid-based validation index, a centroid-based validation index that is called a centroid-based shadow value (CSV) has been developed.  Although both are similar, the CS...

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Main Author: Budiaji, Weksi (Author)
Format: EJournal Article
Published: Universitas Ahmad Dahlan, 2019-04-05.
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042 |a dc 
100 1 0 |a Budiaji, Weksi  |e author 
100 1 0 |e contributor 
245 0 0 |a Medoid-based shadow value validation and visualization 
260 |b Universitas Ahmad Dahlan,   |c 2019-04-05. 
500 |a https://ijain.org/index.php/IJAIN/article/view/326 
520 |a A silhouette index is a well-known measure of an internal criteria validation for the clustering algorithm results. While it is a medoid-based validation index, a centroid-based validation index that is called a centroid-based shadow value (CSV) has been developed.  Although both are similar, the CSV has an additional unique property where an image of a 2-dimensional neighborhood graph is possible. A new internal validation index is proposed in this article in order to create a medoid-based validation that has an ability to visualize the results in a 2-dimensional plot. The proposed index behaves similarly to the silhouette index and produces a network visualization, which is comparable to the neighborhood graph of the CSV. The network visualization has a multiplicative parameter (c) to adjust its edges visibility. Due to the medoid-based, in addition, it is more an appropriate visualization technique for any type of data than a neighborhood graph of the CSV. 
540 |a Copyright (c) 2019 Weksi Budiaji 
540 |a https://creativecommons.org/licenses/by-sa/4.0 
546 |a eng 
690 |a Cluster validation; Cluster visualization; Internal criteria; Medoid; Shadow value 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n International Journal of Advances in Intelligent Informatics; Vol 5, No 2 (2019): July 2019; 76-88 
786 0 |n 2548-3161 
786 0 |n 2442-6571 
787 0 |n https://ijain.org/index.php/IJAIN/article/view/326/ijain_v5i2_p76-78 
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