Medoid-based shadow value validation and visualization
| Main Author: | Budiaji, Weksi |
|---|---|
| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Universitas Ahmad Dahlan
, 2019
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| Subjects: | |
| Online Access: |
http://ijain.org/index.php/IJAIN/article/view/326 http://ijain.org/index.php/IJAIN/article/view/326/ijain_v5i2_p76-78 http://ijain.org/index.php/IJAIN/article/downloadSuppFile/326/82 |
Daftar Isi:
- 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.